Collective behaviour in a square lattice of driven Duffing resonators coupled to van der Pol oscillators

The global and local synchronisation of a square lattice composed of alternating Duffing resonators and van der Pol oscillators coupled through displacement is studied. The lattice acts as a sensing device in which the input signal is characterised by an external driving force that is injected into the system through a subset of the Duffing resonators. The parameters of the system are taken from MEMS devices. The effects of the system parameters, the lattice architecture and size are discussed

A preliminary study into emergent behaviours in a lattice of interacting nonlinear resonators and oscillators

Future sensor arrays will be composed of interacting nonlinear components with complex behaviours with no known analytic solutions. This paper provides a preliminary insight into the expected behaviour through numerical and analytical analysis. Specically, the complex behaviour of a periodically driven nonlinear Duffing resonator coupled elastically to a van der Pol oscillator is investigated as a building block in a 2D lattice of such units with local connectivity. An analytic treatment of the 2-device unit is provided through a two-time-scales approach and the stability of the complex dynamic motion is analysed. The pattern formation characteristics of a 2D lattice composed of these units coupled together through nearest neighbour interactions is analysed numerically for parameters appropriate to a physical realisation through MEMS devices. The emergent patterns of global and cluster synchronisation are investigated with respect to system parameters and lattice size

Brain-inspired conscious computing architecture

What type of artificial systems will claim to be conscious and will claim to experience qualia? The ability to comment upon physical states of a brain-like dynamical system coupled with its environment seems to be sufficient to make claims. The flow of internal states in such system, guided and limited by associative memory, is similar to the stream of consciousness. Minimal requirements for an artificial system that will claim to be conscious were given in form of specific architecture named articon. Nonverbal discrimination of the working memory states of the articon gives it the ability to experience different qualities of internal states. Analysis of the inner state flows of such a system during typical behavioral process shows that qualia are inseparable from perception and action. The role of consciousness in learning of skills, when conscious information processing is replaced by subconscious, is elucidated. Arguments confirming that phenomenal experience is a result of cognitive processes are presented. Possible philosophical objections based on the Chinese room and other arguments are discussed, but they are insufficient to refute claims articon’s claims. Conditions for genuine understanding that go beyond the Turing test are presented. Articons may fulfill such conditions and in principle the structure of their experiences may be arbitrarily close to human

Oscillatory architecture of memory circuits

The coordinated activity between remote brain regions underlies cognition and memory function. Although neuronal oscillations have been proposed as a mechanistic substrate for the coordination of information transfer and memory consolidation during sleep, little is known about the mechanisms that support the widespread synchronization of brain regions and the relationship of neuronal dynamics with other bodily rhythms, such as breathing. During exploratory behavior, the hippocampus and the prefrontal cortex are organized by theta oscillations, known to support memory encoding and retrieval, while during sleep the same structures are dominated by slow oscillations that are believed to underlie the consolidation of recent experiences. The expression of conditioned fear and extinction memories relies on the coordinated activity between the mPFC and the basolateral amygdala (BLA), a neuronal structure encoding associative fear memories. However, to date, the mechanisms allowing this long-range network synchronization of neuronal activity between the mPFC and BLA during fear behavior remain virtually unknown. Using a combination of extracellular recordings and open- and closed-loop optogenetic manipulations, we investigated the oscillatory and coding mechanisms mediating the organization and coupling of the limbic circuit in the awake and asleep brain, as well as during memory encoding and retrieval. We found that freezing, a behavioral expression of fear, is tightly associated with an internally generated brain state that manifests in sustained 4Hz oscillatory dynamics in prefrontal-amygdala circuits. 4Hz oscillations accurately predict the onset and termination of the freezing state. These oscillations synchronize prefrontal-amygdala circuits and entrain neuronal activity to dynamically regulate the development of neuronal ensembles. This enables the precise timing of information transfer between the two structures and the expression of fear responses. Optogenetic induction of prefrontal 4Hz oscillations promotes freezing behavior and the formation of long-lasting fear memory, while closed-loop phase specific manipulations bidirectionally modulate fear expression. Our results unravel a physiological signature of fear memory and identify a novel internally generated brain state, characterized by 4Hz oscillations. This oscillation enables the temporal coordination and information transfer in the prefrontal-amygdala circuit via a phase-specific coding mechanism, facilitating the encoding and expression of fear memory. In the search for the origin of this oscillation, we focused our attention on breathing, the most fundamental and ubiquitous rhythmic activity in life. Using large-scale extracellular recordings from a number of structures, including the medial prefrontal cortex, hippocampus, thalamus, amygdala and nucleus accumbens in mice we identified and characterized the entrainment by breathing of a host of network dynamics across the limbic circuit. We established that fear-related 4Hz oscillations are a state-specific manifestation of this cortical entrainment by the respiratory rhythm. We characterized the translaminar and transregional profile of this entrainment and demonstrated a causal role of breathing in synchronizing neuronal activity and network dynamics between these structures in a variety of behavioral scenarios in the awake and sleep state. We further revealed a dual mechanism of respiratory entrainment, in the form of an intracerebral corollary discharge that acts jointly with an olfactory reafference to coordinate limbic network dynamics, such as hippocampal ripples and cortical UP and DOWN states, involved in memory consolidation. Respiration provides a perennial stream of rhythmic input to the brain. In addition to its role as the condicio sine qua non for life, here we provide evidence that breathing rhythm acts as a global pacemaker for the brain, providing a reference signal that enables the integration of exteroceptive and interoceptive inputs with the internally generated dynamics of the hippocampus and the neocortex. Our results highlight breathing, a perennial rhythmic input to the brain, as an oscillatory scaffold for the functional coordination of the limbic circuit, enabling the segregation and integration of information flow across neuronal networks

Smart chemical sensing microsystem : towards a nose-on-a-chip

The electronic nose is a rudimentary replica of the human olfactory system. However there has been considerable commercial interest in the use of electronic nose systems in application areas such as environmental, medical, security and food industry. In many ways the existing electronic nose systems are considerable inferior when compared to their biological counterparts, lacking in terms of discrimination capability, processing time and environmental adaptation. Here, the aim is to extract biological principles from the mammalian olfactory systems to create a new architecture in order to aid the implementation of a nose-on-a-chip system. The primary feature identified in this study was the nasal chromatography phenomena which may provide significant improvement by producing discriminatory spatio-temporal signals for electronic nose systems. In this project, two different but complimentary groups of systems have been designed and fabricated to investigate the feasibility of generating spatio-temporal signals. The first group of systems include the fast-nose (channel 10 cm x 500 μm2), proto-nose I (channel 1.2 m x 500 μm2) and II (channel 2.4 m x 500 μm2) systems that were build using discrete components. The fast-nose system was used to characterise the discrete sensors prior to use. The proto-nose systems, in many ways, resembles gas chromatography systems. Each proto-nose system consists of two microchannels (with and without coating) and 40 polymer-composite sensors of 10 different materials placed along it. The second group of systems include the hybrid-nose and the aVLSI-nose microsensor arrays assembled with microchannel packages of various lengths (5 cm, 32 cm, 7lcm, 240 cm) to form nose-on-a-chip systems. The hybrid-nose sensor array consists of 80 microsensors built on a 10 mm x 10 mm silicon substrate while the aVLSI-nose sensor array consists of 70 microsensors built on a 10 mm x 5 mm silicon substrate using standard CMOS process with smart integrated circuitries. The microchannel packages were fabricated using the Perfactory microstereolithography system. The most advanced microchannel package contains a 2.4 m x 500 J.lm2 microchannel with an external size of only 36 mm x 27 mm x 7 mm. The nose-on-a-chip system achieved miniaturisation and eliminates the need for any external processing circuitries while achieving the same capability of producing spatio-temporal signals. Using a custom-designed vapour test station and data acquisition electronics, these systems were evaluated with simple analytes and complex odours. The experimental results were in-line with the simulation results. On the coated proto-nose II system, a 25 s temporal delay was observed on the toluene vapour pulse compared to ethanol vapour pulse; this is significant compared to the uncoated system where no delay difference was obtained. Further testing with 8 analyte mixtures substantiated that spatio-temporal signals can be extracted from both the coated proto-nose and nose-on-a-chip (hybrid-nose sensor array with 2.4 m long microchannel) systems. This clearly demonstrates that these systems were capable of imitating certain characteristics of the biological olfactory system. Using only the temporal data, classification was performed with principal components analysis. The results reinforced that these additional temporal signals were useful to improve discrimination analysis which is not possible with any existing sensor-based electronic nose system. In addition, fast responding polymer-composite sensors were achieved exhibiting response times of less than 100 ms. Other biological characteristics relating to stereolfaction (two nostrils sniffing at different rates), sniffing rate (flow velocity) and duration (pulse width) were also investigated. The results converge with the biological observations that stereolfaction and sniffing at higher rate and duration improve discrimination. Last but not least, the characterisation of the smart circuitries on the aVLSI-nose show that it is possible to achieve better performance through the use of smart processing circuitries incorporating a novel DC-offset cancellation technique to amplify small sensor response with large baseline voltage. The results and theories presented in this study should provide useful contribution for designing a higher-performance electronic nose incorporating biological principles

A microscopic model of signal transduction mechanisms: olfaction

This thesis recognizes that: in many systems the initial small molecule - receptor recognition processes, and thus signal transduction, is not fully understood to the highest level of scientifc explanation and prediction. One such example of this is olfaction. Molecules cannot necessarily be predicted from a smell, and similarly a smell from molecules. Better understanding of these initial steps, would have important repercussions, especially in the field of rational drug design. So in general the thesis proves the physical feasibility and potential of a novel and generic signaling model, and in particular looks at those processes in olfaction. The conjecture 'Could humans recognize odours through phonon assisted tunneling?' is tested. This is based on the idea (Turin, 1996) that the nose recognizes an odorant's vibrations (phonons) via inelastic electron tunneling (IETS). The nose thus acts as a 'meat spectroscope'. First the background biology of the olfactory system is evaluated, then the conjecture is posed as a soluble problem. Traditional physics ideas are reconciled with the biological environment. It is proven that no physics based objections hold against the working of this new mechanism, thus a predictive and explanatory theory is now introduced to the field. The parameters of odorant discrimination are explored. In particular the 'Huang-Rhys factor' is modeled as a measure of the electron-phonon coupling integral to signal transduction. Several approaches are considered, 'odorant spectra' is created. Objections to the conjecture are considered, in particular the apparent paradox of enantiomer discrimination. The apparent paradox is shown to be obsolete. A correlation between a certain type of flexibility and whether enantiomer pairs smell the same is found. A rule is established: The members of an enantiomer pair will smell alike (type 1) when the molecules are rigid, and will smell different (type 2) when they are flexible. This flexibility refers to a particular property of six-membered rings. A consequence of this finding leads to the investigation of certain steroids in correlation to their bio-effects, and it is found that similar features are apparent, thus the mechanism of biological IETS is applied to other systems

2022 roadmap on neuromorphic computing and engineering

Modern computation based on von Neumann architecture is now a mature cutting-edge science. In the von Neumann architecture, processing and memory units are implemented as separate blocks interchanging data intensively and continuously. This data transfer is responsible for a large part of the power consumption. The next generation computer technology is expected to solve problems at the exascale with 10$^{18}$ calculations each second. Even though these future computers will be incredibly powerful, if they are based on von Neumann type architectures, they will consume between 20 and 30 megawatts of power and will not have intrinsic physically built-in capabilities to learn or deal with complex data as our brain does. These needs can be addressed by neuromorphic computing systems which are inspired by the biological concepts of the human brain. This new generation of computers has the potential to be used for the storage and processing of large amounts of digital information with much lower power consumption than conventional processors. Among their potential future applications, an important niche is moving the control from data centers to edge devices. The aim of this roadmap is to present a snapshot of the present state of neuromorphic technology and provide an opinion on the challenges and opportunities that the future holds in the major areas of neuromorphic technology, namely materials, devices, neuromorphic circuits, neuromorphic algorithms, applications, and ethics. The roadmap is a collection of perspectives where leading researchers in the neuromorphic community provide their own view about the current state and the future challenges for each research area. We hope that this roadmap will be a useful resource by providing a concise yet comprehensive introduction to readers outside this field, for those who are just entering the field, as well as providing future perspectives for those who are well established in the neuromorphic computing community