Spikes, Synchrony, and Attentive Learning by Laminar Thalamocortical Circuits

This article develops the Synchronous Matching Adaptive Resonance Theory (SMART) neural model to explain how the brain may coordinate multiple levels of thalamocortical and corticocortical processing to rapidly learn, and stably remember, important information about a changing world. The model clarifies how bottom-up and top-down processes work together to realize this goal, notably how processes of learning, expectation, attention, resonance, and synchrony are coordinated. The model hereby clarifies, for the first time, how the following levels of brain organization coexist to realize cognitive processing properties that regulate fast learning and stable memory of brain representations: single cell properties, such as spiking dynamics, spike-timing-dependent plasticity (STDP), and acetylcholine modulation; detailed laminar thalamic and cortical circuit designs and their interactions; aggregate cell recordings, such as current-source densities and local field potentials; and single cell and large-scale inter-areal oscillations in the gamma and beta frequency domains. In particular, the model predicts how laminar circuits of multiple cortical areas interact with primary and higher-order specific thalamic nuclei and nonspecific thalamic nuclei to carry out attentive visual learning and information processing. The model simulates how synchronization of neuronal spiking occurs within and across brain regions, and triggers STDP. Matches between bottom-up adaptively filtered input patterns and learned top-down expectations cause gamma oscillations that support attention, resonance, and learning. Mismatches inhibit learning while causing beta oscillations during reset and hypothesis testing operations that are initiated in the deeper cortical layers. The generality of learned recognition codes is controlled by a vigilance process mediated by acetylcholine.

Spiking Dynamics during Perceptual Grouping in the Laminar Circuits of Visual Cortex

Grouping of collinear boundary contours is a fundamental process during visual perception. Illusory contour completion vividly illustrates how stable perceptual boundaries interpolate between pairs of contour inducers, but do not extrapolate from a single inducer. Neural models have simulated how perceptual grouping occurs in laminar visual cortical circuits. These models predicted the existence of grouping cells that obey a bipole property whereby grouping can occur inwardly between pairs or greater numbers of similarly oriented and co-axial inducers, but not outwardly from individual inducers. These models have not, however, incorporated spiking dynamics. Perceptual grouping is a challenge for spiking cells because its properties of collinear facilitation and analog sensitivity to inducer configurations occur despite irregularities in spike timing across all the interacting cells. Other models have demonstrated spiking dynamics in laminar neocortical circuits, but not how perceptual grouping occurs. The current model begins to unify these two modeling streams by implementing a laminar cortical network of spiking cells whose intracellular temporal dynamics interact with recurrent intercellular spiking interactions to quantitatively simulate data from neurophysiological experiments about perceptual grouping, the structure of non-classical visual receptive fields, and gamma oscillations.

Towards a Unified Theory of Neocortex: Laminar Cortical Circuits for Vision and Cognition

A key goal of computational neuroscience is to link brain mechanisms to behavioral functions. The present article describes recent progress towards explaining how laminar neocortical circuits give rise to biological intelligence. These circuits embody two new and revolutionary computational paradigms: Complementary Computing and Laminar Computing. Circuit properties include a novel synthesis of feedforward and feedback processing, of digital and analog processing, and of pre-attentive and attentive processing. This synthesis clarifies the appeal of Bayesian approaches but has a far greater predictive range that naturally extends to self-organizing processes. Examples from vision and cognition are summarized. A LAMINART architecture unifies properties of visual development, learning, perceptual grouping, attention, and 3D vision. A key modeling theme is that the mechanisms which enable development and learning to occur in a stable way imply properties of adult behavior. It is noted how higher-order attentional constraints can influence multiple cortical regions, and how spatial and object attention work together to learn view-invariant object categories. In particular, a form-fitting spatial attentional shroud can allow an emerging view-invariant object category to remain active while multiple view categories are associated with it during sequences of saccadic eye movements. Finally, the chapter summarizes recent work on the LIST PARSE model of cognitive information processing by the laminar circuits of prefrontal cortex. LIST PARSE models the short-term storage of event sequences in working memory, their unitization through learning into sequence, or list, chunks, and their read-out in planned sequential performance that is under volitional control. LIST PARSE provides a laminar embodiment of Item and Order working memories, also called Competitive Queuing models, that have been supported by both psychophysical and neurobiological data. These examples show how variations of a common laminar cortical design can embody properties of visual and cognitive intelligence that seem, at least on the surface, to be mechanistically unrelated.

From Synapse to Self: Spikes, Synchrony, and Attentive Learning by Laminar Thalamocortical Circuits

How do our brains transform the "blooming buzzing confusion" of daily experience into a coherent sense of self that can learn and selectively attend to important information? How do local signals at multiple processing stages, none of which has a global view of brain dynamics or behavioral outcomes, trigger learning at multiple synaptic sites when appropriate, and prevent learning when inappropriate, to achieve useful behavioral goals in a continually changing world? How does the brain allow synaptic plasticity at a remarkably rapid rate, as anyone who has gone to an exciting movie is readily aware, yet also protect useful memories from catastrophic forgetting? A neural model provides a unified answer by explaining and quantitatively simulating data about single cell biophysics and neurophysiology, laminar neuroanatomy, aggregate cell recordings (current-source densities, local field potentials), large-scale oscillations (beta, gamma), and spike-timing dependent plasticity, and functionally linking them all to cognitive information processing requirements.

Emergence of Tri-Phasic Muscle Activation from the Non-linear Interactions of Central and Spinal Neural Network Circuits

The origin of the tri-phasic burst pattern, observed in the EMGs of opponent muscles during rapid self-terminated movements, has been controversial. Here we show by computer simulation that the pattern emerges from interactions between a central neural trajectory controller (VITE circuit) and a peripheral neuromuscularforce controller (FLETE circuit). Both neural models have been derived from simple functional constraints that have led to principled explanations of a wide variety of behavioral and neurobiological data, including, as shown here, the generation of tri-phasic bursts.

Systematic delay-driven power optimisation and power-driven delay optimisation of combinational circuits

With the proliferation of mobile wireless communication and embedded systems, the energy efficiency becomes a major design constraint. The dissipated energy is often referred as the product of power dissipation and the input-output delay. Most of electronic design automation techniques focus on optimising only one of these parameters either power or delay. Industry standard design flows integrate systematic methods of optimising either area or timing while for power consumption optimisation one often employs heuristics which are characteristic to a specific design. In this work we answer three questions in our quest to provide a systematic approach to joint power and delay Optimisation. The first question of our research is: How to build a design flow which incorporates academic and industry standard design flows for power optimisation? To address this question, we use a reference design flow provided by Synopsys and integrate in this flow academic tools and methodologies. The proposed design flow is used as a platform for analysing some novel algorithms and methodologies for optimisation in the context of digital circuits. The second question we answer is: Is possible to apply a systematic approach for power optimisation in the context of combinational digital circuits? The starting point is a selection of a suitable data structure which can easily incorporate information about delay, power, area and which then allows optimisation algorithms to be applied. In particular we address the implications of a systematic power optimisation methodologies and the potential degradation of other (often conflicting) parameters such as area or the delay of implementation. Finally, the third question which this thesis attempts to answer is: Is there a systematic approach for multi-objective optimisation of delay and power? A delay-driven power and power-driven delay optimisation is proposed in order to have balanced delay and power values. This implies that each power optimisation step is not only constrained by the decrease in power but also the increase in delay. Similarly, each delay optimisation step is not only governed with the decrease in delay but also the increase in power. The goal is to obtain multi-objective optimisation of digital circuits where the two conflicting objectives are power and delay. The logic synthesis and optimisation methodology is based on AND-Inverter Graphs (AIGs) which represent the functionality of the circuit. The switching activities and arrival times of circuit nodes are annotated onto an AND-Inverter Graph under the zero and a non-zero-delay model. We introduce then several reordering rules which are applied on the AIG nodes to minimise switching power or longest path delay of the circuit at the pre-technology mapping level. The academic Electronic Design Automation (EDA) tool ABC is used for the manipulation of AND-Inverter Graphs. We have implemented various combinatorial optimisation algorithms often used in Electronic Design Automation such as Simulated Annealing and Uniform Cost Search Algorithm. Simulated Annealing (SMA) is a probabilistic meta heuristic for the global optimization problem of locating a good approximation to the global optimum of a given function in a large search space. We used SMA to probabilistically decide between moving from one optimised solution to another such that the dynamic power is optimised under given delay constraints and the delay is optimised under given power constraints. A good approximation to the global optimum solution of energy constraint is obtained. Uniform Cost Search (UCS) is a tree search algorithm used for traversing or searching a weighted tree, tree structure, or graph. We have used Uniform Cost Search Algorithm to search within the AIG network, a specific AIG node order for the reordering rules application. After the reordering rules application, the AIG network is mapped to an AIG netlist using specific library cells. Our approach combines network re-structuring, AIG nodes reordering, dynamic power and longest path delay estimation and optimisation and finally technology mapping to an AIG netlist. A set of MCNC Benchmark circuits and large combinational circuits up to 100,000 gates have been used to validate our methodology. Comparisons for power and delay optimisation are made with the best synthesis scripts used in ABC. Reduction of 23% in power and 15% in delay with minimal overhead is achieved, compared to the best known ABC results. Also, our approach is also implemented on a number of processors with combinational and sequential components and significant savings are achieved.

Control circuits for avalanche photodiodes

Avalanche Photodiodes (APDs) have been used in a wide range of low light sensing applications such as DNA sequencing, quantum key distribution, LIDAR and medical imaging. To operate the APDs, control circuits are required to achieve the desired performance characteristics. This thesis presents the work on development of three control circuits including a bias circuit, an active quench and reset circuit and a gain control circuit all of which are used for control and performance enhancement of the APDs. The bias circuit designed is used to bias planar APDs for operation in both linear and Geiger modes. The circuit is based on a dual charge pumps configuration and operates from a 5 V supply. It is capable of providing milliamp load currents for shallow-junction planar APDs that operate up to 40 V. With novel voltage regulators, the bias voltage provided by the circuit can be accurately controlled and easily adjusted by the end user. The circuit is highly integrable and provides an attractive solution for applications requiring a compact integrated APD device. The active quench and reset circuit is designed for APDs that operate in Geiger-mode and are required for photon counting. The circuit enables linear changes in the hold-off time of the Geiger-mode APD (GM-APD) from several nanoseconds to microseconds with a stable setting step of 6.5 ns. This facilitates setting the optimal `afterpulse-free' hold-off time for any GM-APD via user-controlled digital inputs. In addition this circuit doesn’t require an additional monostable or pulse generator to reset the detector, thus simplifying the circuit. Compared to existing solutions, this circuit provides more accurate and simpler control of the hold-off time while maintaining a comparable maximum count-rate of 35.2 Mcounts/s. The third circuit designed is a gain control circuit. This circuit is based on the idea of using two matched APDs to set and stabilize the gain. The circuit can provide high bias voltage for operating the planar APD, precisely set the APD’s gain (with the errors of less than 3%) and compensate for the changes in the temperature to maintain a more stable gain. The circuit operates without the need for external temperature sensing and control electronics thus lowering the system cost and complexity. It also provides a simpler and more compact solution compared to previous designs. The three circuits designed in this project were developed independently of each other and are used for improving different performance characteristics of the APD. Further research on the combination of the three circuits will produce a more compact APD-based solution for a wide range of applications.

Photonic integrated circuits for the generation of coherent optical signals

The demand for optical bandwidth continues to increase year on year and is being driven primarily by entertainment services and video streaming to the home. Current photonic systems are coping with this demand by increasing data rates through faster modulation techniques, spectrally efficient transmission systems and by increasing the number of modulated optical channels per fibre strand. Such photonic systems are large and power hungry due to the high number of discrete components required in their operation. Photonic integration offers excellent potential for combining otherwise discrete system components together on a single device to provide robust, power efficient and cost effective solutions. In particular, the design of optical modulators has been an area of immense interest in recent times. Not only has research been aimed at developing modulators with faster data rates, but there has also a push towards making modulators as compact as possible. Mach-Zehnder modulators (MZM) have proven to be highly successful in many optical communication applications. However, due to the relatively weak electro-optic effect on which they are based, they remain large with typical device lengths of 4 to 7 mm while requiring a travelling wave structure for high-speed operation. Nested MZMs have been extensively used in the generation of advanced modulation formats, where multi-symbol transmission can be used to increase data rates at a given modulation frequency. Such nested structures have high losses and require both complex fabrication and packaging. In recent times, it has been shown that Electro-absorption modulators (EAMs) can be used in a specific arrangement to generate Quadrature Phase Shift Keying (QPSK) modulation. EAM based QPSK modulators have increased potential for integration and can be made significantly more compact than MZM based modulators. Such modulator designs suffer from losses in excess of 40 dB, which limits their use in practical applications. The work in this thesis has focused on how these losses can be reduced by using photonic integration. In particular, the integration of multiple lasers with the modulator structure was considered as an excellent means of reducing fibre coupling losses while maximising the optical power on chip. A significant difficultly when using multiple integrated lasers in such an arrangement was to ensure coherence between the integrated lasers. The work investigated in this thesis demonstrates for the first time how optical injection locking between discrete lasers on a single photonic integrated circuit (PIC) can be used in the generation of coherent optical signals. This was done by first considering the monolithic integration of lasers and optical couplers to form an on chip optical power splitter, before then examining the behaviour of a mutually coupled system of integrated lasers. By operating the system in a highly asymmetric coupling regime, a stable phase locking region was found between the integrated lasers. It was then shown that in this stable phase locked region the optical outputs of each laser were coherent with each other and phase locked to a common master laser.

Test-pattern selection for screening small-delay defects in very-deep submicrometer integrated circuits

Timing-related defects are major contributors to test escapes and in-field reliability problems for very-deep submicrometer integrated circuits. Small delay variations induced by crosstalk, process variations, power-supply noise, as well as resistive opens and shorts can potentially cause timing failures in a design, thereby leading to quality and reliability concerns. We present a test-grading technique that uses the method of output deviations for screening small-delay defects (SDDs). A new gate-delay defect probability measure is defined to model delay variations for nanometer technologies. The proposed technique intelligently selects the best set of patterns for SDD detection from an n-detect pattern set generated using timing-unaware automatic test-pattern generation (ATPG). It offers significantly lower computational complexity and excites a larger number of long paths compared to a current generation commercial timing-aware ATPG tool. Our results also show that, for the same pattern count, the selected patterns provide more effective coverage ramp-up than timing-aware ATPG and a recent pattern-selection method for random SDDs potentially caused by resistive shorts, resistive opens, and process variations. © 2010 IEEE.

Oscillations by minimal bacterial suicide circuits reveal hidden facets of host-circuit physiology.

Synthetic biology seeks to enable programmed control of cellular behavior though engineered biological systems. These systems typically consist of synthetic circuits that function inside, and interact with, complex host cells possessing pre-existing metabolic and regulatory networks. Nevertheless, while designing systems, a simple well-defined interface between the synthetic gene circuit and the host is frequently assumed. We describe the generation of robust but unexpected oscillations in the densities of bacterium Escherichia coli populations by simple synthetic suicide circuits containing quorum components and a lysis gene. Contrary to design expectations, oscillations required neither the quorum sensing genes (luxR and luxI) nor known regulatory elements in the P(luxI) promoter. Instead, oscillations were likely due to density-dependent plasmid amplification that established a population-level negative feedback. A mathematical model based on this mechanism captures the key characteristics of oscillations, and model predictions regarding perturbations to plasmid amplification were experimentally validated. Our results underscore the importance of plasmid copy number and potential impact of "hidden interactions" on the behavior of engineered gene circuits - a major challenge for standardizing biological parts. As synthetic biology grows as a discipline, increasing value may be derived from tools that enable the assessment of parts in their final context.

Magnetophoretic circuits for digital control of single particles and cells.

The ability to manipulate small fluid droplets, colloidal particles and single cells with the precision and parallelization of modern-day computer hardware has profound applications for biochemical detection, gene sequencing, chemical synthesis and highly parallel analysis of single cells. Drawing inspiration from general circuit theory and magnetic bubble technology, here we demonstrate a class of integrated circuits for executing sequential and parallel, timed operations on an ensemble of single particles and cells. The integrated circuits are constructed from lithographically defined, overlaid patterns of magnetic film and current lines. The magnetic patterns passively control particles similar to electrical conductors, diodes and capacitors. The current lines actively switch particles between different tracks similar to gated electrical transistors. When combined into arrays and driven by a rotating magnetic field clock, these integrated circuits have general multiplexing properties and enable the precise control of magnetizable objects.

Activation in mesolimbic and visuospatial neural circuits elicited by smoking cues: evidence from functional magnetic resonance imaging.

OBJECTIVE: The authors sought to increase understanding of the brain mechanisms involved in cigarette addiction by identifying neural substrates modulated by visual smoking cues in nicotine-deprived smokers. METHOD: Event-related functional magnetic resonance imaging (fMRI) was used to detect brain activation after exposure to smoking-related images in a group of nicotine-deprived smokers and a nonsmoking comparison group. Subjects viewed a pseudo-random sequence of smoking images, neutral nonsmoking images, and rare targets (photographs of animals). Subjects pressed a button whenever a rare target appeared. RESULTS: In smokers, the fMRI signal was greater after exposure to smoking-related images than after exposure to neutral images in mesolimbic dopamine reward circuits known to be activated by addictive drugs (right posterior amygdala, posterior hippocampus, ventral tegmental area, and medial thalamus) as well as in areas related to visuospatial attention (bilateral prefrontal and parietal cortex and right fusiform gyrus). In nonsmokers, no significant differences in fMRI signal following exposure to smoking-related and neutral images were detected. In most regions studied, both subject groups showed greater activation following presentation of rare target images than after exposure to neutral images. CONCLUSIONS: In nicotine-deprived smokers, both reward and attention circuits were activated by exposure to smoking-related images. Smoking cues are processed like rare targets in that they activate attentional regions. These cues are also processed like addictive drugs in that they activate mesolimbic reward regions.

Frontal-striatal circuits in cognitive aging: Evidence for caudate involvement

Changes in cognition with aging have been claimed to be due in large part to a decline in frontal lobe function. However, at our present state of knowledge, the emphasis on the frontal lobes to the exclusion of the rest of the frontal-striatal circuits of which they are a part is unwarranted. To argue this point, I consider another anatomical candidate within these circuits, the caudate. Evidence is presented that the caudate decreases in size with age as much as the frontal lobes and that damage to either the frontal lobes or the caudate is accompanied by declines in inhibitory processes, executive control, and cognitive speed similar to those seen in normal aging. Separating the unique contributions of the frontal lobes and the caudate to these circuits is difficult but should be the focus of future studies of the biological basis of cognitive aging.

Huntingtin is required for normal excitatory synapse development in cortical and striatal circuits.

Huntington's disease (HD) is a neurodegenerative disease caused by the expansion of a poly-glutamine (poly-Q) stretch in the huntingtin (Htt) protein. Gain-of-function effects of mutant Htt have been extensively investigated as the major driver of neurodegeneration in HD. However, loss-of-function effects of poly-Q mutations recently emerged as potential drivers of disease pathophysiology. Early synaptic problems in the excitatory cortical and striatal connections have been reported in HD, but the role of Htt protein in synaptic connectivity was unknown. Therefore, we investigated the role of Htt in synaptic connectivity in vivo by conditionally silencing Htt in the developing mouse cortex. When cortical Htt function was silenced, cortical and striatal excitatory synapses formed and matured at an accelerated pace through postnatal day 21 (P21). This exuberant synaptic connectivity was lost over time in the cortex, resulting in the deterioration of synapses by 5 weeks. Synaptic decline in the cortex was accompanied with layer- and region-specific reactive gliosis without cell loss. To determine whether the disease-causing poly-Q mutation in Htt affects synapse development, we next investigated the synaptic connectivity in a full-length knock-in mouse model of HD, the zQ175 mouse. Similar to the cortical conditional knock-outs, we found excessive excitatory synapse formation and maturation in the cortices of P21 zQ175, which was lost by 5 weeks. Together, our findings reveal that cortical Htt is required for the correct establishment of cortical and striatal excitatory circuits, and this function of Htt is lost when the mutant Htt is present.