Retinal adaptation to object motion

Due to fixational eye movements, the image on the retina is always in motion, even when one views a stationary scene. When an object moves within the scene, the corresponding patch of retina experiences a different motion trajectory than the surrounding region. Certain retinal ganglion cells respond selectively to this condition, when the motion in the cell's receptive field center is different from that in the surround. Here we show that this response is strongest at the very onset of differential motion, followed by gradual adaptation with a time course of several seconds. Different subregions of a ganglion cell's receptive field can adapt independently. The circuitry responsible for differential motion adaptation lies in the inner retina. Several candidate mechanisms were tested, and the adaptation most likely results from synaptic depression at the synapse from bipolar to ganglion cell. Similar circuit mechanisms may act more generally to emphasize novel features of a visual stimulus.     

A tuneable attractor underlies yeast respiratory dynamics

Our understanding of the molecular structure and function in the budding yeast, Saccharomyces cerevisiae, surpasses that of all other eukaryotic cells. However, the fundamental properties of the complex processes and their control systems have been difficult to reconstruct from detailed dissection of their molecular components. Spontaneous oscillatory dynamics observed in self-synchronized continuous cultures is pervasive, involves much of the cellular network, and provides unique insights into integrative cell physiology. Here, in non-invasive experiments in vivo, we exploit these oscillatory dynamics to analyse the global timing of the cellular network to show the presence of a low-order chaotic component. Although robust to a wide range of environmental perturbations, the system responds and reacts to the imposition of harsh environmental conditions, in this case low pH, by dynamic re-organization of respiration, and this feeds upwards to affect cell division. These complex dynamics can be represented by a tuneable attractor that orchestrates cellular complexity and coherence to the environment.     

The evolutionary dynamics of influenza A virus adaptation to mammalian hosts

Few questions on infectious disease are more important than understanding how and why avian influenza A viruses successfully emerge in mammalian populations, yet little is known about the rate and nature of the virus’ genetic adaptation in new hosts. Here, we measure, for the first time, the genomic rate of adaptive evolution of swine influenza viruses (SwIV) that originated in birds. By using a curated dataset of more than 24 000 human and swine influenza gene sequences, including 41 newly characterized genomes, we reconstructed the adaptive dynamics of three major SwIV lineages (Eurasian, EA; classical swine, CS; triple reassortant, TR). We found that, following the transfer of the EA lineage from birds to swine in the late 1970s, EA virus genes have undergone substantially faster adaptive evolution than those of the CS lineage, which had circulated among swine for decades. Further, the adaptation rates of the EA lineage antigenic haemagglutinin and neuraminidase genes were unexpectedly high and similar to those observed in human influenza A. We show that the successful establishment of avian influenza viruses in swine is associated with raised adaptive evolution across the entire genome for many years after zoonosis, reflecting the contribution of multiple mutations to the coordinated optimization of viral fitness in a new environment. This dynamics is replicated independently in the polymerase genes of the TR lineage, which established in swine following separate transmission from non-swine hosts.     

The dynamics of visual adaptation to faces

Several recent demonstrations using visual adaptation have revealed high-level aftereffects for complex patterns including faces. While traditional aftereffects involve perceptual distortion of simple attributes such as orientation or colour that are processed early in the visual cortical hierarchy, face adaptation affects perceived identity and expression, which are thought to be products of higher-order processing. And, unlike most simple aftereffects, those involving faces are robust to changes in scale, position and orientation between the adapting and test stimuli. These differences raise the question of how closely related face aftereffects are to traditional ones. Little is known about the build-up and decay of the face aftereffect, and the similarity of these dynamic processes to traditional aftereffects might provide insight into this relationship. We examined the effect of varying the duration of both the adapting and test stimuli on the magnitude of perceived distortions in face identity. We found that, just as with traditional aftereffects, the identity aftereffect grew logarithmically stronger as a function of adaptation time and exponentially weaker as a function of test duration. Even the subtle aspects of these dynamics, such as the power-law relationship between the adapting and test durations, closely resembled that of other aftereffects. These results were obtained with two different sets of face stimuli that differed greatly in their low-level properties. We postulate that the mechanisms governing these shared dynamics may be dissociable from the responses of feature-selective neurons in the early visual cortex.     

Influence of rapid growth on skeletal adaptation to exercise

During rapid growth, increased body weight and muscle strength result in increased loads on bone. Bone adapts to these increased strains by increasing bone modeling and remodeling. As the growth rate decreases, bone that was formed as a result of these adaptations continues to mineralize and "catch up", and bone modeling and remodeling decreases. Bone benefits of exercise in childhood are reported in some studies, although we observed less BMC gain at trabecular-rich sites during the peri-pubertal period in children who jumped than those who did not. Data from 13 existing pediatric exercise studies were compiled to determine whether similar patterns of age-related bone changes could be identified, and whether the bone benefit of exercise differed depending upon pubertal stage. The benefit of exercise on total body BMC gains occurred across all ages, whereas greater exercise-induced gains at the spine and hip were observed in younger children compared to older children. The majority of studies found a positive effect of exercise on bone, but typically this involved limiting the analysis to specific sub-populations (i.e., higher calcium intake, lower baseline activity levels, smaller body size). Limitations of the studies published to date are discussed.     

A change in conformational dynamics underlies the activation of Eph receptor tyrosine kinases

Eph receptor tyrosine kinases (RTKs) mediate numerous developmental processes. Their activity is regulated by auto-phosphorylation on two tyrosines within the juxtamembrane segment (JMS) immediately N-terminal to the kinase domain (KD). Here, we probe the molecular details of Eph kinase activation through mutational analysis, X-ray crystallography and NMR spectroscopy on auto-inhibited and active EphB2 and EphA4 fragments. We show that a Tyr750Ala gain-of-function mutation in the KD and JMS phosphorylation independently induce disorder of the JMS and its dissociation from the KD. Our X-ray analyses demonstrate that this occurs without major conformational changes to the KD and with only partial ordering of the KD activation segment. However, conformational exchange for helix alphaC in the N-terminal KD lobe and for the activation segment, coupled with increased inter-lobe dynamics, is observed upon kinase activation in our NMR analyses. Overall, our results suggest that a change in inter-lobe dynamics and the sampling of catalytically competent conformations for helix alphaC and the activation segment rather than a transition to a static active conformation underlies Eph RTK activation.     

The binding of learning to action in motor adaptation

In motor tasks, errors between planned and actual movements generally result in adaptive changes which reduce the occurrence of similar errors in the future. It has commonly been assumed that the motor adaptation arising from an error occurring on a particular movement is specifically associated with the motion that was planned. Here we show that this is not the case. Instead, we demonstrate the binding of the adaptation arising from an error on a particular trial to the motion experienced on that same trial. The formation of this association means that future movements planned to resemble the motion experienced on a given trial benefit maximally from the adaptation arising from it. This reflects the idea that actual rather than planned motions are assigned 'credit' for motor errors because, in a computational sense, the maximal adaptive response would be associated with the condition credited with the error. We studied this process by examining the patterns of generalization associated with motor adaptation to novel dynamic environments during reaching arm movements in humans. We found that these patterns consistently matched those predicted by adaptation associated with the actual rather than the planned motion, with maximal generalization observed where actual motions were clustered. We followed up these findings by showing that a novel training procedure designed to leverage this newfound understanding of the binding of learning to action, can improve adaptation rates by greater than 50%. Our results provide a mechanistic framework for understanding the effects of partial assistance and error augmentation during neurologic rehabilitation, and they suggest ways to optimize their use.     

A hierarchical probabilistic model for rapid object categorization in natural scenes

Humans can categorize objects in complex natural scenes within 100-150 ms. This amazing ability of rapid categorization has motivated many computational models. Most of these models require extensive training to obtain a decision boundary in a very high dimensional (e.g., ～6,000 in a leading model) feature space and often categorize objects in natural scenes by categorizing the context that co-occurs with objects when objects do not occupy large portions of the scenes. It is thus unclear how humans achieve rapid scene categorization.To address this issue, we developed a hierarchical probabilistic model for rapid object categorization in natural scenes. In this model, a natural object category is represented by a coarse hierarchical probability distribution (PD), which includes PDs of object geometry and spatial configuration of object parts. Object parts are encoded by PDs of a set of natural object structures, each of which is a concatenation of local object features. Rapid categorization is performed as statistical inference. Since the model uses a very small number (～100) of structures for even complex object categories such as animals and cars, it requires little training and is robust in the presence of large variations within object categories and in their occurrences in natural scenes. Remarkably, we found that the model categorized animals in natural scenes and cars in street scenes with a near human-level performance. We also found that the model located animals and cars in natural scenes, thus overcoming a flaw in many other models which is to categorize objects in natural context by categorizing contextual features. These results suggest that coarse PDs of object categories based on natural object structures and statistical operations on these PDs may underlie the human ability to rapidly categorize scenes.     

Molecular microcircuitry underlies functional specification in a basal ganglia circuit dedicated to vocal learning

Similarities between speech and birdsong make songbirds advantageous for investigating the neurogenetics of learned vocal communication--a complex phenotype probably supported by ensembles of interacting genes in cortico-basal ganglia pathways of both species. To date, only FoxP2 has been identified as critical to both speech and birdsong. We performed weighted gene coexpression network analysis on microarray data from singing zebra finches to discover gene ensembles regulated during vocal behavior. We found ～2,000 singing-regulated genes comprising three coexpression groups unique to area X, the basal ganglia subregion dedicated to learned vocalizations. These contained known targets of human FOXP2 and potential avian targets. We validated biological pathways not previously implicated in vocalization. Higher-order gene coexpression patterns, rather than expression levels, molecularly distinguish area X from the ventral striato-pallidum during singing. The previously unknown structure of singing-driven networks enables prioritization of molecular interactors that probably bear on human motor disorders, especially those affecting speech.     

A rapid mixing-photocrosslinking technique to study the dynamics of nucleic acid-protein interactions

A rapid mixing-photocrosslinking technique has been developed to investigate the kinetics of protein-nucleic acid interactions. With this technique, binding of nucleic acid to protein is first synchronized by rapid mixing in a stopped-flow apparatus. The intermediates formed at different stages of the binding process are then "frozen" by photocrosslinking with a 10-microseconds uv light pulse at various times after mixing. By analyzing structural changes of these intermediates as a function of time, one can obtain the information concerning the dynamic aspects of the interaction. This technique may also be applied to other macromolecular interactions in biological systems.     

A model of bone adaptation as an optimization process

The internal bone adaptation of the proximal femur is considered. A three-dimensional finite element model of the proximal femur is used. The bone remodeling in this work is numerically described by an evolutionary remodeling scheme with anisotropic material parameters and time-dependent loading. The memory of past loading is included in the model to account for the delay in the bone response from the load changes. The remodeling rate equation is derived from the structural optimization task of maximizing the stiffness in each time step. Additional information can be extracted from the optimization process; the remodeling equilibrium parameter where no apposition or resorption takes place, is defined as the element optimality conditions and the optimal design is used as an initial design for the onset of the remodeling simulation. Two examples of bone adaptation resulting from load changes are given, and the irreversible nature of the model is illustrated.     

SNAP-25 modulation of calcium dynamics underlies differences in GABAergic and glutamatergic responsiveness to depolarization

SNAP-25 is a component of the SNARE complex implicated in synaptic vesicle exocytosis. In this study, we demonstrate that hippocampal GABAergic synapses, both in culture and in brain, lack SNAP-25 and are resistant to the action of botulinum toxins type A and E, which cleave this SNARE protein. Relative to glutamatergic neurons, which express SNAP-25, GABAergic cells were characterized by a higher calcium responsiveness to depolarization. Exogenous expression of SNAP-25 in GABAergic interneurons lowered calcium responsiveness, and SNAP-25 silencing in glutamatergic neurons increased calcium elevations evoked by depolarization. Expression of SNAP-25(1-197) but not of SNAP-25(1-180) inhibited calcium responsiveness, pointing to the involvement of the 180-197 residues in the observed function. These data indicate that SNAP-25 is crucial for the regulation of intracellular calcium dynamics and, possibly, of network excitability. SNAP-25 is therefore a multifunctional protein that participates in exocytotic function both at the mechanistic and at the regulatory level.     

Influence of learning on range expansion and adaptation to novel habitats

Learning has been postulated to ‘drive’ evolution, but its influence on adaptive evolution in heterogeneous environments has not been formally examined. We used a spatially explicit individual‐based model to study the effect of learning on the expansion and adaptation of a species to a novel habitat. Fitness was mediated by a behavioural trait (resource preference), which in turn was determined by both the genotype and learning. Our findings indicate that learning substantially increases the range of parameters under which the species expands and adapts to the novel habitat, particularly if the two habitats are separated by a sharp ecotone (rather than a gradient). However, for a broad range of parameters, learning reduces the degree of genetically‐based local adaptation following the expansion and facilitates maintenance of genetic variation within local populations. Thus, in heterogeneous environments learning may facilitate evolutionary range expansions and maintenance of the potential of local populations to respond to subsequent environmental changes.     

The process of adaptation of flour beetles to new environments

Five populations derived from a composite, genetically heterogeneous strain of the flour beetle, Tribolium castaneum, were selected on new diets (dog food, powdered rice, brewers' yeast, wheat flour and oats) for 13–16 generations. A control population was reared on the standard medium (flour + 5% brewers' yeast). Adaptedness was measured in terms of (1) fitness parameters (survival and developmental time), (2) amylase activity levels (amylase is an essential digestive enzyme in flour beetles) and (3) food preference behavior.There were significant temporal trends in fitness components in the selected populations. Survival was initially low but increased with time. Developmental time decreased in later generations of selection. The control population showed the smallest increase in survival and no decrease in developmental time. When tested at the end of the experiment, survival to adulthood of eggs from each selected population on its selective diet was higher than that of control eggs. On the standard medium, no differences in survival among populations were detected. These results suggest that the improvement in fitness may indicate adaptation to the new environments created by the different food media.Amylase activity also increased temporally in 4 selected populations but not in the control (nor on unenriched wheat flour). Tests at the end of the experiment, however, suggest that this increase was, in large part, environmentally induced. We found no evidence that an adaptive genetic change in amylase regulation took place.There were no temporal trends in food-preference behavior during the selection process.     

Biochemical adaptation to rapid temperature changes in scombrid red blood cell enzymes

The physiological adaptations of skipjack tuna lead to 10 degrees C changes in blood temperature every few seconds. The change in reaction rate of red blood cell LDH, MDH and GAPD to change in temperature are large under saturating substrate conditions but under intra-cellular substrate conditions reaction rate is almost independent of temperature. It seems likely that the biochemical effects observed are mediated through changes in Km with temperature. Three species related to the skipjack, but lacking its extreme physiological adaptations, had many of the biochemical adaptations seen in the skipjack. The primitive ancestor of the skipjack probably had the biochemical preadaptations needed to allow the physiological evolution seen in this lineage.     

A neural model for generating and learning a rapid movement sequence

 In this article, a neural model for generating and learning a rapid ballistic movement sequence in two-dimensional (2D) space is presented and evaluated in the light of some considerations about handwriting generation. The model is based on a central nucleus (called a planning space) consisting of a fully connected grid of leaky integrators simulating neurons, and reading an input vector Ξ (t) which represents the external movement of the end effector. The movement sequencing results in a succession of motor strokes whose instantiation is controlled by the global activation of the planning space as defined by a competitive interaction between the neurons of the grid. Constraints such as spatial accuracy and movement time are exploited for the correct synchronization of the impulse commands. These commands are then fed into a neuromuscular synergy whose output is governed by a delta lognormal equation. Each movement sequence is memorized originally as a symbolic engram representing the sequence of the principal reference points of the 2D movement. These points, called virtual targets, correspond to the targets of each single rapid motor stroke composing the movement sequence. The task during the learning phase is to detect the engram corresponding to a new observed movement; the process is controlled by the dynamics of the neural grid. Received: 16 March 1995/Accepted in revised form: 25 July 1995