Neurophysiological findings relevant to echolocation in marine animals

A review of echolocation mechanisms in marine mammals, chiefly porpoises, is given. Data cover peripheral auditory and central neurophysiological specializations favorable to the analysis of echolocating clicks and their echoes. Conclusions show (1) signals are received from 50 up to at least 135 kHz, (2) sound is received through the mandible skin, and (3) the midbrain sites are insensitive to low frequencies (below 6 kHz)

Thermodynamic and transport properties of frozen and reacting pH2-oH2 mixtures

Application of experimental state data and spectroscopic term values shows that the thermodynamic and transport properties of reacting pH2-oH2 mixtures are considerably different than those of chemically frozen pH2 at temperatures below 300 R. Calculated H-S data also show that radiation-induced pH2-oH2 equilibration at constant enthalpy produces a temperature drop of at least 28 R, corresponding to an ideal shaft work loss of 15% or more for a turbine operating downstream from the point of conversion. Aside from differences in thermodynamic and transport properties, frozen pH2-oH2 mixtures may differ from pure pH2 on a purely hydrodynamical basis

Neutral coding - A report based on an NRP work session

Neural coding by impulses and trains on single and multiple channels, and representation of information in nonimpulse carrier

A Self-Organizing Neural Model of Motor Equivalent Reaching and Tool Use by a Multijoint Arm

This paper describes a self-organizing neural model for eye-hand coordination. Called the DIRECT model, it embodies a solution of the classical motor equivalence problem. Motor equivalence computations allow humans and other animals to flexibly employ an arm with more degrees of freedom than the space in which it moves to carry out spatially defined tasks under conditions that may require novel joint configurations. During a motor babbling phase, the model endogenously generates movement commands that activate the correlated visual, spatial, and motor information that are used to learn its internal coordinate transformations. After learning occurs, the model is capable of controlling reaching movements of the arm to prescribed spatial targets using many different combinations of joints. When allowed visual feedback, the model can automatically perform, without additional learning, reaches with tools of variable lengths, with clamped joints, with distortions of visual input by a prism, and with unexpected perturbations. These compensatory computations occur within a single accurate reaching movement. No corrective movements are needed. Blind reaches using internal feedback have also been simulated. The model achieves its competence by transforming visual information about target position and end effector position in 3-D space into a body-centered spatial representation of the direction in 3-D space that the end effector must move to contact the target. The spatial direction vector is adaptively transformed into a motor direction vector, which represents the joint rotations that move the end effector in the desired spatial direction from the present arm configuration. Properties of the model are compared with psychophysical data on human reaching movements, neurophysiological data on the tuning curves of neurons in the monkey motor cortex, and alternative models of movement control.National Science Foundation (IRI 90-24877); Office of Naval Research (N00014-92-J-1309); Air Force Office of Scientific Research (F49620-92-J-0499); National Science Foundation (IRI 90-24877

A Self-Organizing Neural Network for Learning a Body-Centered Invariant Representation of 3-D Target Position

This paper describes a self-organizing neural network that rapidly learns a body-centered representation of 3-D target positions. This representation remains invariant under head and eye movements, and is a key component of sensory-motor systems for producing motor equivalent reaches to targets (Bullock, Grossberg, and Guenther, 1993).National Science Foundation (IRI-87-16960, IRI-90-24877); Air Force Office of Scientific Research (F49620-92-J-0499

Neural Representations for Sensory-Motor Control, III: Learning a Body-Centered Representation of 3-D Target Position

A neural model is described of how the brain may autonomously learn a body-centered representation of 3-D target position by combining information about retinal target position, eye position, and head position in real time. Such a body-centered spatial representation enables accurate movement commands to the limbs to be generated despite changes in the spatial relationships between the eyes, head, body, and limbs through time. The model learns a vector representation--otherwise known as a parcellated distributed representation--of target vergence with respect to the two eyes, and of the horizontal and vertical spherical angles of the target with respect to a cyclopean egocenter. Such a vergence-spherical representation has been reported in the caudal midbrain and medulla of the frog, as well as in psychophysical movement studies in humans. A head-centered vergence-spherical representation of foveated target position can be generated by two stages of opponent processing that combine corollary discharges of outflow movement signals to the two eyes. Sums and differences of opponent signals define angular and vergence coordinates, respectively. The head-centered representation interacts with a binocular visual representation of non-foveated target position to learn a visuomotor representation of both foveated and non-foveated target position that is capable of commanding yoked eye movementes. This head-centered vector representation also interacts with representations of neck movement commands to learn a body-centered estimate of target position that is capable of commanding coordinated arm movements. Learning occurs during head movements made while gaze remains fixed on a foveated target. An initial estimate is stored and a VOR-mediated gating signal prevents the stored estimate from being reset during a gaze-maintaining head movement. As the head moves, new estimates arc compared with the stored estimate to compute difference vectors which act as error signals that drive the learning process, as well as control the on-line merging of multimodal information.Air Force Office of Scientific Research (F49620-92-J-0499); National Science Foundation (IRI -87-16960, IRI-90-24877); Office of Naval Research (N00014-92-J-l309

Asymptotically Optimal Quantum Circuits for d-level Systems

As a qubit is a two-level quantum system whose state space is spanned by |0>, |1>, so a qudit is a d-level quantum system whose state space is spanned by |0>,...,|d-1>. Quantum computation has stimulated much recent interest in algorithms factoring unitary evolutions of an n-qubit state space into component two-particle unitary evolutions. In the absence of symmetry, Shende, Markov and Bullock use Sard's theorem to prove that at least C 4^n two-qubit unitary evolutions are required, while Vartiainen, Moettoenen, and Salomaa (VMS) use the QR matrix factorization and Gray codes in an optimal order construction involving two-particle evolutions. In this work, we note that Sard's theorem demands C d^{2n} two-qudit unitary evolutions to construct a generic (symmetry-less) n-qudit evolution. However, the VMS result applied to virtual-qubits only recovers optimal order in the case that d is a power of two. We further construct a QR decomposition for d-multi-level quantum logics, proving a sharp asymptotic of Theta(d^{2n}) two-qudit gates and thus closing the complexity question for all d-level systems (d finite.) Gray codes are not required, and the optimal Theta(d^{2n}) asymptotic also applies to gate libraries where two-qudit interactions are restricted by a choice of certain architectures.Comment: 18 pages, 5 figures (very detailed.) MatLab files for factoring qudit unitary into gates in MATLAB directory of source arxiv format. v2: minor change

Can the mid-Holocene provide suitable models for rewilding the landscape in Britain?

Palaeoecologists have been encouraging us to think about the relevance of the Holocene fossil record for nature conservation for many years (e.g. Buckland 1993) but this information seems slow to filter through to the conservation community. Indeed, Willis et al. (2005) report that recently published biodiversity reports and policy documents rarely look back more than 50 years and may ignore the historical context entirely. This has been a lost opportunity for understanding ecological systems. Many natural processes occur over timescales that confound our attempts to understand them, so the vast temporal perspective provided by palaeoecological studies can provide important guidance for nature conservation (Willis & Birks 2006). However, accurate vegetation mapping is difficult enough in modern landscapes (Cherrill & McLean 1999), so the challenge of describing prehistoric environments is immeasurably greater. Nevertheless, pioneering work in the mid 20th century showed that pollen and spores extracted from peat bogs were so perfectly preserved thatthey could be used to demonstrate sequences of vegetation change since the last glaciation (Godwin 1956). Since then, the science has burgeoned: ancient deposits of beetles, snails, fungal spores and plant macrofossils add to the picture, as does the chemistry of ancient lake sediments (Bell & Walker 2004). Many questions still remain to be answered by this fascinating research and one aspect has received considerable attention in the last decade. This concerns the nature of the ‘primeval’ landscapes, in other words our understanding of natural systems prior to significant human impact. The debate was kindled by a thesis by the Dutch forest ecologist Frans Vera in 2000 (see also Vera & Buissink 2007). Vera effectively challenged established views about the primeval landscapes and argued that the refutation, and the resulting alternative landscape models, had critical importance for modern conservation practice. Vera’s thesis is focused on the pre-Neolithic (ca 8000-5000bp) landscape in the lowlands of central and western Europe, with the assumption that this period represents an almost pristine or ‘natural’ state which should provide a suitable conservation benchmark. Vera contends (i) that this landscape was not closed woodland but a relatively open park-like mosaic of wood and grassland,and (ii) that large wild herbivores were an essential driving force behind woodland-grassland vegetation cycles. The advocacy in his argument and the timing of the publication, when grazingwas seen as increasingly important in conservation in Europe, have combined to raise the profile of this issue. If Vera is correct, the open park-like landscapes were inherited rather than created by people; this may have implications for conservation practice in Europe. The adoption of Vera’s ideas into conservation management plans in the UK (see Box 1) gives an indication of the influence that this work has had. Indeed, Vera’s ideas have been described as a ‘challenge to orthodox thinking’ (Miller 2002) and considerable debate has been stimulated centering on the ecological validity of Vera’s hypothesis and its relevance for modern conservation. In this article, we attempt to address these issues on the basis of results from a literature review, web-debate and discussions with Dutch and British ecologists, prepared for English Nature with a view to informing conservation strategies (Hodder & Bullock 2005a)