903 resultados para Cortical Circuits
Synchronized Oscillations During Cooperative Feature Lining in a Cortical Model of Visual Perception
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A neural network model of synchronized oscillations in visual cortex is presented to account for recent neurophysiological findings that such synchronization may reflect global properties of the stimulus. In these experiments, synchronization of oscillatory firing responses to moving bar stimuli occurred not only for nearby neurons, but also occurred between neurons separated by several cortical columns (several mm of cortex) when these neurons shared some receptive field preferences specific to the stimuli. These results were obtained for single bar stimuli and also across two disconnected, but colinear, bars moving in the same direction. Our model and computer simulations obtain these synchrony results across both single and double bar stimuli using different, but formally related, models of preattentive visual boundary segmentation and attentive visual object recognition, as well as nearest-neighbor and randomly coupled models.
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This article describes further evidence for a new neural network theory of biological motion perception. The theory clarifies why parallel streams Vl --> V2, Vl --> MT, and Vl --> V2 --> MT exist for static form and motion form processing among the areas Vl, V2, and MT of visual cortex. The theory suggests that the static form system (Static BCS) generates emergent boundary segmentations whose outputs are insensitive to direction-ofcontrast and insensitive to direction-of-motion, whereas the motion form system (Motion BCS) generates emergent boundary segmentations whose outputs are insensitive to directionof-contrast but sensitive to direction-of-motion. The theory is used to explain classical and recent data about short-range and long-range apparent motion percepts that have not yet been explained by alternative models. These data include beta motion; split motion; gamma motion and reverse-contrast gamma motion; delta motion; visual inertia; the transition from group motion to element motion in response to a Ternus display as the interstimulus interval (ISI) decreases; group motion in response to a reverse-contrast Ternus display even at short ISIs; speed-up of motion velocity as interflash distance increases or flash duration decreases; dependence of the transition from element motion to group motion on stimulus duration and size; various classical dependencies between flash duration, spatial separation, ISI, and motion threshold known as Korte's Laws; dependence of motion strength on stimulus orientation and spatial frequency; short-range and long-range form-color interactions; and binocular interactions of flashes to different eyes.
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A neural network model of synchronized oscillator activity in visual cortex is presented in order to account for recent neurophysiological findings that such synchronization may reflect global properties of the stimulus. In these recent experiments, it was reported that synchronization of oscillatory firing responses to moving bar stimuli occurred not only for nearby neurons, but also occurred between neurons separated by several cortical columns (several mm of cortex) when these neurons shared some receptive field preferences specific to the stimuli. These results were obtained not only for single bar stimuli but also across two disconnected, but colinear, bars moving in the same direction. Our model and computer simulations obtain these synchrony results across both single and double bar stimuli. For the double bar case, synchronous oscillations are induced in the region between the bars, but no oscillations are induced in the regions beyond the stimuli. These results were achieved with cellular units that exhibit limit cycle oscillations for a robust range of input values, but which approach an equilibrium state when undriven. Single and double bar synchronization of these oscillators was achieved by different, but formally related, models of preattentive visual boundary segmentation and attentive visual object recognition, as well as nearest-neighbor and randomly coupled models. In preattentive visual segmentation, synchronous oscillations may reflect the binding of local feature detectors into a globally coherent grouping. In object recognition, synchronous oscillations may occur during an attentive resonant state that triggers new learning. These modelling results support earlier theoretical predictions of synchronous visual cortical oscillations and demonstrate the robustness of the mechanisms capable of generating synchrony.
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Air Force Office of Scientific Research (90-0175); Defense Advanced Research Projects Agency (90-0083); Office of Naval Research (N00014-91-J-4100)
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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.
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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.
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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.
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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.
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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.
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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.
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During cortical synaptic development, thalamic axons must establish synaptic connections despite the presence of the more abundant intracortical projections. How thalamocortical synapses are formed and maintained in this competitive environment is unknown. Here, we show that astrocyte-secreted protein hevin is required for normal thalamocortical synaptic connectivity in the mouse cortex. Absence of hevin results in a profound, long-lasting reduction in thalamocortical synapses accompanied by a transient increase in intracortical excitatory connections. Three-dimensional reconstructions of cortical neurons from serial section electron microscopy (ssEM) revealed that, during early postnatal development, dendritic spines often receive multiple excitatory inputs. Immuno-EM and confocal analyses revealed that majority of the spines with multiple excitatory contacts (SMECs) receive simultaneous thalamic and cortical inputs. Proportion of SMECs diminishes as the brain develops, but SMECs remain abundant in Hevin-null mice. These findings reveal that, through secretion of hevin, astrocytes control an important developmental synaptic refinement process at dendritic spines.
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Recent emergence of human connectome imaging has led to a high demand on angular and spatial resolutions for diffusion magnetic resonance imaging (MRI). While there have been significant growths in high angular resolution diffusion imaging, the improvement in spatial resolution is still limited due to a number of technical challenges, such as the low signal-to-noise ratio and high motion artifacts. As a result, the benefit of a high spatial resolution in the whole-brain connectome imaging has not been fully evaluated in vivo. In this brief report, the impact of spatial resolution was assessed in a newly acquired whole-brain three-dimensional diffusion tensor imaging data set with an isotropic spatial resolution of 0.85 mm. It was found that the delineation of short cortical association fibers is drastically improved as well as the definition of fiber pathway endings into the gray/white matter boundary-both of which will help construct a more accurate structural map of the human brain connectome.
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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.
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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.
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The spiking activity of nearby cortical neurons is correlated on both short and long time scales. Understanding this shared variability in firing patterns is critical for appreciating the representation of sensory stimuli in ensembles of neurons, the coincident influences of neurons on common targets, and the functional implications of microcircuitry. Our knowledge about neuronal correlations, however, derives largely from experiments that used different recording methods, analysis techniques, and cortical regions. Here we studied the structure of neuronal correlation in area V4 of alert macaques using recording and analysis procedures designed to match those used previously in primary visual cortex (V1), the major input to V4. We found that the spatial and temporal properties of correlations in V4 were remarkably similar to those of V1, with two notable differences: correlated variability in V4 was approximately one-third the magnitude of that in V1 and synchrony in V4 was less temporally precise than in V1. In both areas, spontaneous activity (measured during fixation while viewing a blank screen) was approximately twice as correlated as visual-evoked activity. The results provide a foundation for understanding how the structure of neuronal correlation differs among brain regions and stages in cortical processing and suggest that it is likely governed by features of neuronal circuits that are shared across the visual cortex.