Human cognition is said to be systematic: cognitive ability generalizes to structurally related behaviours. The connectionist approach to cognitive theorizing has been strongly criticized for its failure to explain systematicity. Demonstrations of generalization notwithstanding, I show that two widely used networks (feedforward and recurrent) do not support systematicity under the condition of local input/output representations. For a connectionist explanation of systematicity, these results leave two choices, either: (1) develop models capable of systematicity under local input/output representations; or (2) justify (...) the choice of similarity-based (nonlocal) component representations sufficient for systematicity. (shrink)

In dynamical systems models feedforward is needed to guide planning and to process unknown and unpredictable events. Feedforward could help Theory of Event Coding (TEC) integrate control processes and could model human performance in action planning in a more flexible and powerful way.

Localizing content in neural networks provides a bridge to understanding the way in which the brain stores and processes information. In this paper, I propose the existence of polytopes in the state space of the hidden layer of feedforward neural networks as vehicles of content. I analyze these geometrical structures from an information-theoretic point of view, invoking mutual information to help define the content stored within them. I establish how this proposal addresses the problem of misclassification and provide a (...) novel solution to the disjunction problem, which hinges on the precise nature of the causal-informational framework for content advocated herein. (shrink)

The central thesis of our target article is that feedback is never necessary in spoken word recognition. In this response we begin by clarifying some terminological issues that have led to a number of misunderstandings. We provide some new arguments that the feedforward model Merge is indeed more parsimonious than the interactive alternatives, and that it provides a more convincing account of the data than alternative models. Finally, we extend the arguments to deal with new issues raised by the (...) commentators such as infant speech perception and neural architecture. (shrink)

Auditory feedback perturbation studies have indicated a link between feedback and feedforward mechanisms in speech production when participants compensate for applied shifts. In spectral perturbation studies, speakers with a higher perceptual auditory acuity typically compensate more than individuals with lower acuity. However, the reaction to feedback perturbation is unlikely to be merely a matter of perceptual acuity but also affected by the prediction and production of precise motor action. This interplay between prediction, perception, and motor execution seems to be (...) crucial for the timing of speech and non-speech motor actions. In this study, to examine the relationship between the responses to temporally perturbed auditory feedback and rhythmic abilities, we tested 45 adult speakers on the one hand with a temporal auditory feedback perturbation paradigm, and on the other hand with rhythm perception and production tasks. The perturbation tasks temporally stretched and compressed segments (onset + vowel or vowel + coda) in fluent speech in real-time. This technique sheds light on the temporal representation and the production flexibility of timing mechanisms in fluent speech with respect to the structure of the syllable. The perception tasks contained staircase paradigms capturing duration discrimination abilities and beat-alignment judgments. The rhythm production tasks consisted of finger tapping tasks taken from the BAASTA tapping battery and additional speech tapping tasks. We found that both auditory acuity and motor stability in finger tapping affected responses to temporal auditory feedback perturbation. In general, speakers with higher auditory acuity and higher motor variability compensated more. However, we observed a different weighting of auditory acuity and motor stability dependent on the prosodic structure of the perturbed sequence and the nature of the response as purely online or adaptive. These findings shed light on the interplay of phonological structure with feedback and feedforward integration for timing mechanisms in speech. (shrink)

Isolated feedforward networks (FFNs) of spiking neurons have been studied extensively for their ability to propagate transient synchrony and asynchronous firing rates, in the presence of activity independent synaptic background noise (Diesmann et al., 1999; van Rossum et al., 2002). In a biologically realistic scenario, however, the FFN should be embedded in a recurrent network, such that the activity in the FFN and the network activity may dynamically interact. Previously, transient synchrony propagating in an FFN was found to destabilize (...) the dynamics of the embedding network (Mehring et al., 2003). Here, we show that by modeling synapses as conductance transients, rather than current sources, it is possible to embed and propagate transient synchrony in the FFN, without destabilizing the background network dynamics. However, the network activity has a strong impact on the type of activity that can be propagated in the embedded FFN. Global synchrony and high firing rates in the embedding network prohibit the propagation of both, synchronous and asynchronous spiking activity. In contrast, asynchronous low-rate network states support the propagation of both, synchronous spiking and asynchro- nous, but only low firing rates. In either case, spiking activity tends to synchronize as it propagates, challenging the feasibility to transmit information in asynchronous firing rates. Finally, asynchronous network activity allows to embed more than one FFN, with the amount of cross talk depending on the degree of overlap in the FFNs. This opens the possibility of computational mechanisms using transient synchrony among the activities in multiple FFNs. (shrink)

Preparing words in speech production is normally a fast and accurate process. We generate them two or three per second in fluent conversation; and overtly naming a clear picture of an object can easily be initiated within 600 msec after picture onset. The underlying process, however, is exceedingly complex. The theory reviewed in this target article analyzes this process as staged and feedforward. After a first stage of conceptual preparation, word generation proceeds through lexical selection, morphological and phonological encoding, (...) phonetic encoding, and articulation itself. In addition, the speaker exerts some degree of output control, by monitoring of self-produced internal and overt speech. The core of the theory, ranging from lexical selection to the initiation of phonetic encoding, is captured in a computational model, called WEAVER++. Both the theory and the computational model have been developed in interaction with reaction time experiments, particularly in picture naming or related word production paradigms, with the aim of accounting for the real-time processing in normal word production. A comprehensive review of theory, model, and experiments is presented. The model can handle some of the main observations in the domain of speech errors (the major empirical domain for most other theories of lexical access), and the theory opens new ways of approaching the cerebral organization of speech production by way of high-temporal-resolution imaging. (shrink)

This is a sketch of the basis and role of consciousness and the minimally required elements and constraints of any setting that may produce consciousness. It proposes that consciousness (as we know it) is a biologically-mediated product of evolved recursive and hierarchically nested representational systems that obey information theoretic principles and Bayesian (probabilistic) feedback and feedforward predictive modeling processes.

The neural representation of a repeated stimulus is the standard against which a deviant stimulus is measured in the brain, giving rise to the well-known mismatch response. It has been suggested that individuals with dyslexia have poor implicit memory for recently repeated stimuli, such as the train of standards in an oddball paradigm. Here, we examined how the neural representation of a standard emerges over repetitions, asking whether there is less sensitivity to repetition and/or less accrual of “standardness” over successive (...) repetitions in dyslexia. We recorded magnetoencephalography as adults with and without dyslexia were passively exposed to speech syllables in a roving-oddball design. We performed time-resolved multivariate decoding of the MEG sensor data to identify the neural signature of standard vs. deviant trials, independent of stimulus differences. This “multivariate mismatch” was equally robust and had a similar time course in the two groups. In both groups, standards generated by as few as two repetitions were distinct from deviants, indicating normal sensitivity to repetition in dyslexia. However, only in the control group did standards become increasingly different from deviants with repetition. These results suggest that many of the mechanisms that give rise to neural adaptation as well as mismatch responses are intact in dyslexia, with the possible exception of a putatively predictive mechanism that successively integrates recent sensory information into feedforward processing. (shrink)

Following the pioneering studies of the receptive field (RF), the concept gained further significance for visual perception by the discovery of input effects from beyond the classical RF. These studies demonstrated that neuronal responses could be modulated by stimuli outside their RFs, consistent with the perception of induced brightness, color, orientation, and motion. Lesion scotomata are similarly modulated perceptually from the surround by RFs that have migrated from the interior to the outer edge of the scotoma and in this way (...) provide filling-in of the void. Large RFs are advantageous to this task. In higher visual areas, such as the middle temporal and inferotemporal lobe, RFs increase in size and lose most of their retinotopic organization while encoding increasingly complex features. Whereas lowerlevel RFs mediate perceptual filling-in, contour integration, and figure–ground segregation, RFs at higher levels serve the perception of grouping by common fate, biological motion, and other biologically relevant stimuli, such as faces. Studies in alert monkeys while freely viewing natural scenes showed that classical and nonclassical RFs cooperate in forming representations of the visual world. Today, our understanding of the mechanisms underlying the RF is undergoing a quantum leap. What had started out as a hierarchical feedforward concept for simple stimuli, such as spots, lines, and bars, now refers to mechanisms involving ascending, descending, and lateral signal flow. By extension of the bottom-up paradigm, RFs are nowadays understood as adaptive processors, enabling the predictive coding of complex scenes. Top-down effects guiding attention and tuned to task-relevant information complement the bottom-up analysis. (shrink)

Extensive training with a musical instrument results in the automatisation of the bodily operations needed to manipulate the instrument: the performer no longer has to consciously think about the instrument while playing. The ability of the performer to automate operations on the instrument is due to sensorimotor mechanisms that can predict changes in the state of the body and the instrument in response to motor commands. But how strong are these mechanisms? To what extent can we alter the structure of (...) the instrument before they disappear? We performed an exploratory study to understand whether and how sensorimotor predictions survive instrument modification. We asked seven professional violinists to perform repertoire pieces and sight-reading exercises on four different violins: their own, a cheap violin, a small violin, and a violin whose strings had been put on in reverse order. We performed a series of quantitative investigations on performance intonation and duration, and on bowing gestures and errors. The analysis revealed that participants struggled adapting to the altered instruments, suggesting that prediction mechanisms are a function of instrument configuration. In particular, the analysis of bowing errors, intonation, and of performance duration suggested that the performance with the reverse violin was much less fluent and precise than the performer's own instrument; the performance with the small violin was also sub-standard though to a lesser extent. We also observed that violinists were differently affected by instrument modifications, suggesting that the capability to adapt to a new instrument is highly personal. (shrink)

Despite the recent surge in research on, and interest in, synesthesia, the mechanism underlying this condition is still unknown. Feedforward mechanisms involving overlapping receptive fields of sensory neurons as well as feedback mechanisms involving a lack of signal disinhibition have been proposed. Here I show that a broad range of studies of developmental synesthesia indicate that the mechanism underlying the phenomenon may involve reinstatement of brain activity in different sensory or cognitive streams in a way that is similar to (...) what happens during memory retrieval of semantically associated items. In the paper’s final sections I look at the relevance of synesthesia research, given the memory model, to our understanding of multisensory perception and common mapping patterns. (shrink)

It is possible to learn multiple layers of non-linear features by backpropagating error derivatives through a feedforward neural network. This is a very effective learning procedure when there is a huge amount of labeled training data, but for many learning tasks very few labeled examples are available. In an effort to overcome the need for labeled data, several different generative models were developed that learned interesting features by modeling the higher order statistical structure of a set of input vectors. (...) One of these generative models, the restricted Boltzmann machine (RBM), has no connections between its hidden units and this makes perceptual inference and learning much simpler. More significantly, after a layer of hidden features has been learned, the activities of these features can be used as training data for another RBM. By applying this idea recursively, it is possible to learn a deep hierarchy of progressively more complicated features without requiring any labeled data. This deep hierarchy can then be treated as a feedforward neural network which can be discriminatively fine-tuned using backpropagation. Using a stack of RBMs to initialize the weights of a feedforward neural network allows backpropagation to work effectively in much deeper networks and it leads to much better generalization. A stack of RBMs can also be used to initialize a deep Boltzmann machine that has many hidden layers. Combining this initialization method with a new method for fine-tuning the weights finally leads to the first efficient way of training Boltzmann machines with many hidden layers and millions of weights. (shrink)

Jerry Fodor and Ernest Lepore [(1992) Holism: a shopper's guide, Oxford: Blackwell; (1996) in R. McCauley (Ed.) The Churchlands and their critics , Cambridge: Blackwell] have launched a powerful attack against Paul Churchland's connectionist theory of semantics--also known as state space semantics. In one part of their attack, Fodor and Lepore argue that the architectural and functional idiosyncrasies of connectionist networks preclude us from articulating a notion of conceptual similarity applicable to state space semantics. Aarre Laakso and Gary Cottrell [(1998) (...) in M. A. Gernsbacher & S. Derry (Eds) Proceedings of the 20th Annual Conference of the Cognitive Science Society, Mahway, NJ: Erlbaum; Philosophical Psychology ] 13, 47-76 have recently run a number of simulations on simple feedforward networks and applied a mathematical technique for measuring conceptual similarity in the representational spaces of those networks. Laakso and Cottrell contend that their results decisively refute Fodor and Lepore's criticisms. Paul Churchland [(1998) Journal of Philosophy, 95, 5-32 ] goes further. He uses Laakso and Cottrell's neurosimulations to argue that connectionism does furnish us with all we need to construct a robust theory of semantics and a robust theory of translation. In this paper I shall argue that whereas Laakso and Cottrell's neurocomputational results may provide us with a rebuttal of Fodor and Lepore's argument, Churchland's conclusion is far too optimistic. In particular, I shall try to show that connectionist modelling does not provide any objective criterion for achieving a one-to-one accurate translational mapping across networks. (shrink)

The abstract basis of modern computation is the formal description of a finite state machine, the Universal Turing Machine, based on manipulation of integers and logic symbols. In this contribution to the discourse on the computer-brain analogy, we discuss the extent to which analog computing, as performed by the mammalian brain, is like and unlike the digital computing of Universal Turing Machines. We begin with ordinary reality being a permanent dialog between continuous and discontinuous worlds. So it is with computing, (...) which can be analog or digital, and is often mixed. The theory behind computers is essentially digital, but efficient simulations of phenomena can be performed by analog devices; indeed, any physical calculation requires implementation in the physical world and is therefore analog to some extent, despite being based on abstract logic and arithmetic. The mammalian brain, comprised of neuronal networks, functions as an analog device and has given rise to artificial neural networks that are implemented as digital algorithms but function as analog models would. Analog constructs compute with the implementation of a variety of feedback and feedforward loops. In contrast, digital algorithms allow the implementation of recursive processes that enable them to generate unparalleled emergent properties. We briefly illustrate how the cortical organization of neurons can integrate signals and make predictions analogically. While we conclude that brains are not digital computers, we speculate on the recent implementation of human writing in the brain as a possible digital path that slowly evolves the brain into a genuine (slow) Turing machine. (shrink)

The Cabin Pressure Control System is an essential part of the aviation environmental control system that ensures aircraft structure and flight crew safety. However, the CPCS usually has potential faults of sensors and actuators. To this end, a Simple Adaptive Control- based reconfiguration method is proposed to compensate for the above adverse effects. Some good pressure control performance of CPCS can be achieved by the basic pressure controller when the system is in normal operation. A parallel feedforward compensator is (...) designed to guarantee the closed-loop system’s stability and the almost strictly positive realness of the augmented system. Thus, the simple adaptive controller can be utilized for the CPCS. In particular, the reconfiguration system can update the control law online when the fault occurs without the system identification process. The reference model is obtained by mathematical model linearization after considering the mechanical characteristics of the CPCS. Extensive simulations under various typical fault scenarios are carried out throughout the entire flight envelope of the aircraft from take-off to landing. Simulation results validate the robustness and reconfiguration control capability of the proposed method. (shrink)

To learn a visual code in an unsupervised manner, one may attempt to capture those features of the stimulus set that would contribute significantly to a statistically efficient representation. Paradoxically, all the candidate features in this approach need to be known before statistics over them can be computed. This paradox may be circumvented by confining the repertoire of candidate features to actual scene fragments, which resemble the “what+where” receptive fields found in the ventral visual stream in primates. We describe a (...) single-layer network that learns such fragments from unsegmented raw images of structured objects. The learning method combines fast imprinting in the feedforward stream with lateral interactions to achieve single-epoch unsupervised acquisition of spatially localized features that can support systematic treatment of structured objects [1]. (shrink)

At the phenomenal level, consciousness can be described as a singular, unified field of recursive self-awareness, consistently coherent in a particualr way; that of a subject located both spatially and temporally in an egocentrically-extended domain, such that conscious self-awareness is explicitly characterized by I-ness, now-ness and here-ness. The psychological mechanism underwriting this spatiotemporal self-locatedness and its recursive processing style involves an evolutionary elaboration of the basic orientative reference frame which consistently structures ongoing spatiotemporal self-location computations as i-here-now. Cognition computes action-output (...) in the midst of ongoing movement, and consequently requires a constant self-locating spatiotemporal reference frame as basis for these computations. Over time, constant evolutionary pressures for energy efficiency have encouraged both the proliferation of anticipative feedforward processing mechansims, and the elaboration, at the apex of the sensorimotor processing hierarchy, of self-activating, highly attenuated recursively-feedforward circuitry processing the basic orientational schema independent of external action output. As the primary reference frame of active waking cognition, this recursive i-here-now processing generates a zone of subjective self-awareness in terms of which it feels like something to be oneself here and now. This is consciousness. (shrink)

Predictive coding models of brain processing propose that top-down cortical signals promote efficient neural signaling by carrying predictions about incoming sensory information. These “priors” serve to constrain bottom-up signal propagation where prediction errors are carried via feedforward mechanisms. Depression, traditionally viewed as a disorder characterized by negative cognitive biases, is associated with disrupted reward prediction error encoding and signaling. Accumulating evidence also suggests that depression is characterized by impaired local and long-range prediction signaling across multiple sensory domains. This review (...) highlights the electrophysiological and neuroimaging evidence for disrupted predictive processing in depression. The discussion is framed around the manner in which disrupted generative predictions about the sensorium could lead to depressive symptomatology, including anhedonia and negative bias. In particular, the review focuses on studies of sensory deviance detection and reward processing, highlighting research evidence for both disrupted generative predictions and prediction error signaling in depression. The role of the monoaminergic and glutamatergic systems in predictive coding processes is also discussed. This review provides a novel framework for understanding depression using predictive coding principles and establishes a foundational roadmap for potential future research. (shrink)

Information processing that subserves conscious cognitive functions is thought to involve recurrent signaling through feedforward and feedback loops among hierarchically arranged functional regions of the cerebral cortex. In the current issue of Consciousness and Cognition, Lee et al. report that loss of consciousness, as produced by a bolus injection of the general anesthetic propofol to human volunteers, was accompanied by a decrease in wide-band EEG feedback connectivity from frontal cortex to parietal cortex, confirming a prediction from previous experimental studies. (...) Interestingly, frontoparietal feedback connectivity did not fully recover after the anesthetic effect wore off and the subjects first opened their eyes in response to a verbal command. Possible interpretations of the results and their implications with respect to the neural correlates of consciousness and unconsciousness are discussed. (shrink)

The question of when and how bottom‐up input is integrated with top‐down knowledge has been debated extensively within cognition and perception, and particularly within language processing. A long running debate about the architecture of the spoken‐word recognition system has centered on the locus of lexical effects on phonemic processing: does lexical knowledge influence phoneme perception through feedback, or post‐perceptually in a purely feedforward system? Elman and McClelland (1988) reported that lexically restored ambiguous phonemes influenced the perception of the following (...) phoneme, supporting models with feedback from lexical to phonemic representations. Subsequently, several authors have argued that these results can be fully accounted for by diphone transitional probabilities in a feedforward system (Cairns et al., 1995; Pitt & McQueen, 1998). We report results strongly favoring the original lexical feedback explanation: lexical effects were present even when transitional probability biases were opposite to those of lexical biases. (shrink)

Human adaptive behavior in sensorimotor control is aimed to increase the confidence in feedforward mechanisms when sensory afferents are uncertain. It is thought that these feedforward mechanisms rely on predictions from internal models. We investigate whether the brain uses an internal model of physical laws to help estimate body equilibrium when tactile inputs from the foot sole are depressed by carrying extra weight. As direct experimental evidence for such a model is limited, we used Judoka athletes thought to (...) have built up internal models of external loads as compared with Non-Athlete participants and Dancers. Using electroencephalography, we first tested the hypothesis that the influence of tactile inputs was amplified by descending cortical efferent signals. We compared the amplitude of P1N1 somatosensory cortical potential evoked by electrical stimulation of the foot sole in participants standing still with their eyes closed. We showed smaller P1N1 amplitudes in the Load compared to No Load conditions in both Non-Athletes and Dancers. This decrease neural response to tactile stimulation was associated with greater postural oscillations. By contrast in the Judoka’s group, the neural early response to tactile stimulation was unregulated in the Load condition. This suggests that the brain can selectively increase the functional gain of sensory inputs, during challenging equilibrium tasks when tactile inputs were mechanically depressed by wearing a weighted vest. In Judokas, the activation of regions such as the right posterior inferior parietal cortex as early as the P1N1 is likely the source of the neural responses being maintained similar in both Load and No Load conditions. An overweight internal model stored in the right PPC known to be involved in maintaining a coherent representation of one’s body in space can optimize predictive mechanisms in situations with high balance constraints. This hypothesis has been confirmed by showing that postural reaction evoked by a translation of the support surface on which participants were standing wearing extra-weight was improved in Judokas. (shrink)

Models of dream analysis either assume a continuum of waking and dreaming or the existence of two dissociated realities. Both approaches rely on different methodology. Whereas continuity models are based on content analysis, discontinuity models use a structural approach. In our study, we applied both methods to test specific hypotheses about continuity or discontinuity. We contrasted dream reports of congenitally deaf-mute and congenitally paraplegic individuals with those of non-handicapped controls. Continuity theory would predict that either the deficit itself or compensatory (...) experiences would surface in the dream narrative. We found that dream form and content of sensorially limited persons was indifferent from those of non-handicapped controls. Surprisingly, perceptual representations, even of modalities not experienced during waking, were quite common in the dream reports of our handicapped subjects. Results are discussed with respect to feedforward mechanisms and protoconsciousness theory of dreaming. (shrink)

Looking times and gaze behavior indicate that infants can predict the goal state of an observed simple action event (e.g., object‐directed grasping) already in the first year of life. The present paper mainly focuses on infants’ predictive gaze‐shifts toward the goal of an ongoing action. For this, infants need to generate a forward model of the to‐be‐obtained goal state and to disengage their gaze from the moving agent at a time when information about the action event is still incomplete. By (...) about 6 months of age, infants show goal‐predictive gaze‐shifts, but mainly for familiar actions that they can perform themselves (e.g., grasping) and for familiar agents (e.g., a human hand). Therefore, some theoretical models have highlighted close relations between infants’ ability for action‐goal prediction and their motor development and/or emerging action experience. Recent research indicates that infants can also predict action goals of familiar simple actions performed by non‐human agents (e.g., object‐directed grasping by a mechanical claw) when these agents display agency cues, such as self‐propelled movement, equifinality of goal approach, or production of a salient action effect. This paper provides a review on relevant findings and theoretical models, and proposes that the impacts of action experience and of agency cues can be explained from an action‐event perspective. In particular, infants’ goal‐predictive gaze‐shifts are seen as resulting from an interplay between bottom‐up processing of perceptual information and top‐down influences exerted by event schemata that store information about previously executed or observed actions. (shrink)

Frontoparietal connectivity has been suggested to be important in conscious processing and its interruption is thought to be one mechanism of general anesthesia. Data in animals demonstrate that feedforward processing of information may persist during the anesthetized state, while feedback processing is inhibited. We investigated the directionality and functional organization of frontoparietal connectivity in 10 human subjects anesthetized with propofol on two separate occasions. Multichannel electroencephalography and a computational method of assessing directed functional connectivity were employed. We demonstrate that (...) directed feedback connectivity is diminished with loss of consciousness and returns with responsiveness to verbal command. We also applied the Dendrogram classification method to assess the global organization of directed functional connectivity during consciousness and anesthesia. We demonstrate a state-specific hierarchy and subject-specific subhierarchy in functional organization. These data support the hypothesis that specific states of human consciousness are defined by specific states of frontoparietal connectivity. (shrink)

This paper reviews four significant advances on the feedforward architecture that has dominated discussions of connectionism. The first involves introducing modularity into networks by employing procedures whereby different networks learn to perform different components of a task, and a Gating Network determines which network is best equiped to respond to a given input. The second consists in the use of recurrent inputs whereby information from a previous cycle of processing is made available on later cycles. The third development involves (...) developing compressed representations of strings in which there is no longer an explicit encoding of the components but where information about the structure of the original string can be recovered and so is present functionally. The final advance entails using connectionist learning procedures not just to change weights in networks but to change the patterns used as inputs to the network. These advances significantly increase the usefulness of connectionist networks for modeling human cognitive performance by, among other things, providing tools for explaining the productivity and systematicity of some mental activities, and developing representations that are sensitive to the content they are to represent. (shrink)

The commentaries provide a multitude of perspectives on the theory of lexical access presented in our target article. We respond, on the one hand, to criticisms that concern the embeddings of our model in the larger theoretical frameworks of human performance and of a speaker's multiword sentence and discourse generation. These embeddings, we argue, are either already there or naturally forgeable. On the other hand, we reply to a host of theory-internal issues concerning the abstract properties of our feedforward (...) spreading activation model, which functions without the usual cascading, feedback, and inhibitory connections. These issues also concern the concrete stratification in terms of lexical concepts, syntactic lemmas, and morphophonology. Our response stresses the parsimony of our modeling in the light of its substantial empirical coverage. We elaborate its usefulness for neuroimaging and aphasiology and suggest further cross-linguistic extensions of the model. (shrink)

Observations of ultrafast cognition in human performance challenge intuitive information processing and computation metaphors of cognitive processing. Instances of ultrafast cognition are marked by ultrafast response times of reliable, accurate responses to a relatively complex stimulus. Ultrafast means response times that are as fast as a single feedforward burst of activity across the nervous system connecting eye to hand. Thus the information processing and computation metaphors in question are those in which some amount of time is required to decide (...) and initiate a response, over and above the minimum time required, physiologically, for the eye-hand chain of action potentials—these are metaphors in which the brain does work that has a measurable duration in time. Ultrafast cognition can be explained by synergies spanning the mind and body. Synergies are temporary dynamical structures that anticipate context-appropriate behaviour. An anticipatory state poises the mind and body in symmetry among equivalent options for behaviour, and only a minimal change in context, favouring one option over any other, is sufficient to break symmetry and enact an ultrafast cognitive response. (shrink)

Social circumstances often impinge on later generations in a socio-economic manner, giving children an uneven start in life. Overfeeding and overeating might not be an exception. The pathways might be complex but one direct mechanism could be genomic imprinting and loss of imprinting. An intergenerational "feedforward" control loop has been proposed, that links grandparental nutrition with the grandchild's growth. The mechanism has been speculated to be a specific response, e.g. to their nutritional state, directly modifying the setting of the (...) gametic imprint on one or more genes. This study raises the question: Can overnutrition during a child's slow growth period trigger such direct mechanisms and partly determine mortality?Data were collected by following-up a cohort born in 1905 in Överkalix parish, northernmost Sweden. The probands were characterised by their parents' or grandparents' access to food during their own slow growth period. Availability of food in the area was defined by referring to historical data on harvests and food prices, records of local community meetings and general historical facts. (shrink)

This research examined the experiences of authors of academic journal articles in the educational sector of all eight universities in Finland. The ethical principles of peer review and best and worst review processes were in focus. Data were gathered by electronic questionnaire, which was completed by 121 respondents who represented well the heterogeneity of the staff in the educational sector. Out of nine ethical principles honesty, constructiveness, and impartiality were appreciated but promptness, balance, and diplomacy were criticized. According to two (...) open questions, a third of authors praised and blamed reviewers as experts and non-experts. The accuracy of feedback was more often present in the best rather than in the worst experienced review processes. Journals’ editors and their decision-making called forth more negative than positive accounts. The results were discussed in the context of ethical codes for reviewers and researchers’ findings regarding the ethical responsibilities to promote good science with thorough, appropriate, and honest feedback and feedforward. (shrink)

Automatic Generation Control in modern power systems is getting complex, due to intermittency in the output power of multiple sources along with considerable digressions in the loads and system parameters. To address this problem, this paper proposes an approach to calculate Power System Restoration Indices of a 2-area thermal-hydro restructured power system. This study also highlights the necessary ancillary service requirements for the system under a deregulated environment to cater to large-scale power failures and entire system outages. An abrupt change (...) in consumer load demands and disturbances in any control region of a multiarea system causes severe fluctuations in frequency and interarea power exchanges. However, simple Proportional and Integral controllers are most prevalent in the literature to effectively resolve AGC issues, while its integral gain is smaller due to the larger overshoot in transient performance. Therefore, an attempt has been made with a novel control strategy, known as the pseudoderivative feedforward with feedback controller, is developed to keep the interarea power exchanges and the frequency to the specified limits after load changes. A PDFF controller is designed and implemented using the flower pollination algorithm to obtain optimal dynamic performance for different types of potential power flows in a restructured power system under investigation. The proposed PDFF controller localizes the zero at an optimal place that reduces the rise time of the step-response to reduce the excessive overshoot and gives much better dynamic performances as compared to the PI control structure. The Integral Square Error is considered as a performance criterion to derive the optimized gain of the PDFF control structure using FPA. Different PSRI are computed based on the transient response of the 2-area deregulated multisource system and different restoration measures to be taken are also discussed. The simulation results clearly show that the proposed approach is very powerful in decreasing the frequency and tie-power digressions under different load perturbations. (shrink)