Direction Of Information Transfer Research Articles

Analysis of the lag effect of embankment dam seepage based on delayed mutual information

Environmental variables, such as the upstream level, significantly affect the embankment dam seepage lag time. The lag effect should, therefore, be given adequate consideration when determining the saturation line and establishing a mathematical model for seepage. At present, however, the lag time is mainly estimated qualitatively. A method for analyzing the seepage lag effect is presented herein based on the mutual information principle of information science theory, wherein the upstream water level is considered an information source and water level of the seepage pressure is considered an information function point. The method explores application of the directed information transfer index (DITI) of mutual information in order to establish an information transfer model between seepage levels of measurement points and upstream levels of the embankment dam. Furthermore, an extreme value of the DITI function is adopted as the judging criterion to determine the lag time of the influence of the upstream level on corresponding seepage levels. Results obtained through analysis of an engineering case study, demonstrate the effectiveness and feasibility of the proposed method.

Features of the development of artificial intelligence at the present stage

The features of the intelligent logical systems have been discussed. Their comparison with the activity of neural networks has been made. The processes of forming new knowledge in the logical systems and accumulating data in neural networks by organizing a system of concepts have been explained. It has been noted that filling the base of data and rules in logical systems is a process that requires significant resources and therefore has a limited application range. On the contrary, the accumulation of information in extensive neural networks by connecting it to a huge number of agents could provide for effective machine learning and opens up new perspectives for creating artificial intelligence systems. Although teaching the formal descriptions, the usage of abstractions and quantitative calculations to neural systems can present a difficult problem. The prospects for the planetary mind formation and the further development of the planetary intellectual system are considered. The process of increasing the number of elements of neural systems was held back by the ambiguity of the solution before. But, the multiplicity of solutions did not bother the creators of giant neural networks associated with a huge audience. First of all, they were hardly aware of the importance of the solution uniqueness because resolving the problems a person always develops a lot of different scenarios. The possibility of the emergence of artificial intelligence comparable to a natural one in his capabilities has been discussed. The problems of teaching the expert systems and neural networks, how they were defined in the past and what has changed later are explained. The usage of fuzzy logic which is able to form a language of communication with neural networks, free from the need for double translation into natural languages and to simplify the direct transfer of information between a person’s brain and a network may be of a particular interest. Neural networks based on fuzzy neurons which are able to combine the capabilities of expert logical systems and neurocomputers are discussed.

A two-phase copula entropy-based multiobjective optimization approach to hydrometeorological gauge network design

Hydrometeorological data are needed for obtaining point and areal mean, quantifying the spatial variability of hydrometeorological variables, and calibration and verification of hydrometeorological models. Hydrometeorological networks are utilized to collect such data. Since data collection is expensive, it is essential to design an optimal network based on the minimal number of hydrometeorological stations in order to reduce costs. This study proposes a two-phase copula entropy- based multiobjective optimization approach that includes: (1) copula entropy-based directional information transfer (CDIT) for clustering the potential hydrometeorological gauges into several groups, and (2) multiobjective method for selecting the optimal combination of gauges for regionalized groups. Although entropy theory has been employed for network design before, the joint histogram method used for mutual information estimation has several limitations. The copula entropy-based mutual information (MI) estimation method is shown to be more effective for quantifying the uncertainty of redundant information than the joint histogram (JH) method. The effectiveness of this approach is verified by applying to one type of hydrometeorological gauge network, with the use of three model evaluation measures, including Nash–Sutcliffe Coefficient (NSC), arithmetic mean of the negative copula entropy (MNCE), and MNCE/NSC. Results indicate that the two-phase copula entropy-based multiobjective technique is capable of evaluating the performance of regional hydrometeorological networks and can enable decision makers to develop strategies for water resources management.

Pre-processing and transfer entropy measures in motor neurons controlling limb movements.

Directed information transfer measures are increasingly being employed in modeling neural system behavior due to their model-free approach, applicability to nonlinear and stochastic signals, and the potential to integrate repetitions of an experiment. Intracellular physiological recordings of graded synaptic potentials provide a number of additional challenges compared to spike signals due to non-stationary behaviour generated through extrinsic processes. We therefore propose a method to overcome this difficulty by using a preprocessing step based on Singular Spectrum Analysis (SSA) to remove nonlinear trends and discontinuities. We apply the method to intracellular recordings of synaptic responses of identified motor neurons evoked by stimulation of a proprioceptor that monitors limb position in leg of the desert locust. We then apply normalized delayed transfer entropy measures to neural responses evoked by displacements of the proprioceptor, the femoral chordotonal organ, that contains sensory neurones that monitor movements about the femoral-tibial joint. We then determine the consistency of responses within an individual recording of an identified motor neuron in a single animal, between repetitions of the same experiment in an identified motor neurons in the same animal and in repetitions of the same experiment from the same identified motor neuron in different animals. We found that delayed transfer entropy measures were consistent for a given identified neuron within and between animals and that they predict neural connectivity for the fast extensor tibiae motor neuron.

Basolateral Amygdala to Orbitofrontal Cortex Projections Enable Cue-Triggered Reward Expectations.

To make an appropriate decision, one must anticipate potential future rewarding events, even when they are not readily observable. These expectations are generated by using observable information (e.g., stimuli or available actions) to retrieve often quite detailed memories of available rewards. The basolateral amygdala (BLA) and orbitofrontal cortex (OFC) are two reciprocally connected key nodes in the circuitry supporting such outcome-guided behaviors. But there is much unknown about the contribution of this circuit to decision making, and almost nothing known about the whether any contribution is via direct, monosynaptic projections, or the direction of information transfer. Therefore, here we used designer receptor-mediated inactivation of OFC→BLA or BLA→OFC projections to evaluate their respective contributions to outcome-guided behaviors in rats. Inactivation of BLA terminals in the OFC, but not OFC terminals in the BLA, disrupted the selective motivating influence of cue-triggered reward representations over reward-seeking decisions as assayed by Pavlovian-to-instrumental transfer. BLA→OFC projections were also required when a cued reward representation was used to modify Pavlovian conditional goal-approach responses according to the reward's current value. These projections were not necessary when actions were guided by reward expectations generated based on learned action-reward contingencies, or when rewards themselves, rather than stored memories, directed action. These data demonstrate that BLA→OFC projections enable the cue-triggered reward expectations that can motivate the execution of specific action plans and allow adaptive conditional responding.SIGNIFICANCE STATEMENT Deficits anticipating potential future rewarding events are associated with many psychiatric diseases. Presently, we know little about the neural circuits supporting such reward expectation. Here we show that basolateral amygdala to orbitofrontal cortex projections are required for expectations of specific available rewards to influence reward seeking and decision making. The necessity of these projections was limited to situations in which expectations were elicited by reward-predictive cues. These projections therefore facilitate adaptive behavior by enabling the orbitofrontal cortex to use environmental stimuli to generate expectations of potential future rewarding events.

Atypical transistor-based chaotic oscillators: Design, realization, and diversity

In this paper, we show that novel autonomous chaotic oscillators based on one or two bipolar junction transistors and a limited number of passive components can be obtained via random search with suitable heuristics. Chaos is a pervasive occurrence in these circuits, particularly after manual adjustment of a variable resistor placed in series with the supply voltage source. Following this approach, 49 unique circuits generating chaotic signals when physically realized were designed, representing the largest collection of circuits of this kind to date. These circuits are atypical as they do not trivially map onto known topologies or variations thereof. They feature diverse spectra and predominantly anti-persistent monofractal dynamics. Notably, we recurrently found a circuit comprising one resistor, one transistor, two inductors, and one capacitor, which generates a range of attractors depending on the parameter values. We also found a circuit yielding an irregular quantized spike-train resembling some aspects of neural discharge and another one generating a double-scroll attractor, which represent the smallest known transistor-based embodiments of these behaviors. Through three representative examples, we additionally show that diffusive coupling of heterogeneous oscillators of this kind may give rise to complex entrainment, such as lag synchronization with directed information transfer and generalized synchronization. The replicability and reproducibility of the experimental findings are good.

Parallel steady state studies on a milliliter scale accelerate fed-batch bioprocess design for recombinant protein production with Escherichia coli.

In general, fed-batch processes are applied for recombinant protein production with Escherichia coli (E. coli). However, state of the art methods for identifying suitable reaction conditions suffer from severe drawbacks, i.e. direct transfer of process information from parallel batch studies is often defective and sequential fed-batch studies are time-consuming and cost-intensive. In this study, continuously operated stirred-tank reactors on a milliliter scale were applied to identify suitable reaction conditions for fed-batch processes. Isopropyl β-d-1-thiogalactopyranoside (IPTG) induction strategies were varied in parallel-operated stirred-tank bioreactors to study the effects on the continuous production of the recombinant protein photoactivatable mCherry (PAmCherry) with E. coli. Best-performing induction strategies were transferred from the continuous processes on a milliliter scale to liter scale fed-batch processes. Inducing recombinant protein expression by dynamically increasing the IPTG concentration to 100 µM led to an increase in the product concentration of 21% (8.4 g L-1 ) compared to an implemented high-performance production process with the most frequently applied induction strategy by a single addition of 1000 µM IPGT. Thus, identifying feasible reaction conditions for fed-batch processes in parallel continuous studies on a milliliter scale was shown to be a powerful, novel method to accelerate bioprocess design in a cost-reducing manner. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:1426-1435, 2016.

Acute Sleep Deprivation Induces a Local Brain Transfer Information Increase in the Frontal Cortex in a Widespread Decrease Context.

Sleep deprivation (SD) has adverse effects on mental and physical health, affecting the cognitive abilities and emotional states. Specifically, cognitive functions and alertness are known to decrease after SD. The aim of this work was to identify the directional information transfer after SD on scalp EEG signals using transfer entropy (TE). Using a robust methodology based on EEG recordings of 18 volunteers deprived from sleep for 36 h, TE and spectral analysis were performed to characterize EEG data acquired every 2 h. Correlation between connectivity measures and subjective somnolence was assessed. In general, TE showed medium- and long-range significant decreases originated at the occipital areas and directed towards different regions, which could be interpreted as the transfer of predictive information from parieto-occipital activity to the rest of the head. Simultaneously, short-range increases were obtained for the frontal areas, following a consistent and robust time course with significant maps after 20 h of sleep deprivation. Changes during sleep deprivation in brain network were measured effectively by TE, which showed increased local connectivity and diminished global integration. TE is an objective measure that could be used as a potential measure of sleep pressure and somnolence with the additional property of directed relationships.

Brain connectivity in autism spectrum disorder.

Many studies have reported that individuals with autism spectrum disorder (ASD) have different brain connectivity patterns compared with typically developing individuals. However, the results of more recent studies do not unanimously support the traditional view in which individuals with ASD have lower connectivity between distant brain regions and increased connectivity within local brain regions. In this review, we discuss different methods for measuring brain connectivity and how the use of different metrics may contribute to the lack of convergence of investigations of connectivity in ASD. The discrepancy in brain connectivity results across studies may be due to important methodological factors, such as the connectivity measure applied, the age of patients studied, the brain region(s) examined, and the time interval and frequency band(s) in which connectivity was analyzed. We conclude that more sophisticated electroencephalography analytic approaches should be utilized to more accurately infer causation and directionality of information transfer between brain regions, which may show dynamic changes of functional connectivity in the brain. Moreover, further investigations of connectivity with respect to behavior and clinical phenotype are needed to probe underlying brain networks implicated in core deficits of ASD.

"EduKation demenz®". Psychoeducative training program for relatives of people with dementia

During the course of dementia there is frequently a decline in the quality of interpersonal relationships between the patient and the family caregivers. This is mainly caused by a very critical attitude of the family caregiver to the patient and by the limited ability of the family caregiver to empathically communicate with the patient. This relational disorder significantly contributes to the perceived burden of the family caregiver. This study was carried out to investigate whether the ability of family caregivers to empathically communicate can be strengthened, their emotional attitude towards the patient can be improved and their perceived burden and symptoms of depression can be reduced through a special communication-oriented psychoeducational intervention. Within the framework of a controlled study for confounding factors 121 family caregivers participated in a 10-week group intervention "EduKation demenz®," whereas the 93 family caregivers of the control group received detailed self-help literature. The before and after surveys were conducted using a standardized questionnaire. Compared to the control group the intervention group displayed a statistically significant difference in all target parameters: more empathic communication with the patient (confounder-controlled difference of change in the intervention group versus control group 0.69, p = 0.023), a less critical attitude towards the patient (confounder-controlled difference of change in the intervention group versus control group 2.11, p = 0.027), reduction in the perceived burden from disrupted communication (confounder-controlled difference of change in the intervention group versus control group 1.76, p = 0.038) and decreased symptoms of depression for caregivers with ≥ 33 points in the general depression scale (ADS-K, p = 0.028). Family caregivers of people with dementia clearly did not benefit from direct information transfer through the extensive offer of self-help literature to the same extent as the psychoeducational group intervention.

Joint Optimization Schemes for Cooperative Wireless Information and Power Transfer Over Rician Channels

Simultaneous wireless information and power transfer (SWIPT) can lead to uninterrupted network operation by integrating radio frequency (RF) energy harvesting with data communication. In this paper, we consider a two-hop source-relay-destination network and investigate the efficient usage of a decode-and-forward (DF) relay for SWIPT toward the energy-constrained destination. In particular, by assuming a Rician fading environment, we jointly optimize power allocation (PA), relay placement (RP), and power splitting (PS) so as to minimize outage probability under the harvested power constraint at the destination node. We consider the two possible cases of source-to-destination distance: (1) small distance with direct information transfer link; and (2) relatively large distance with no direct reachability. Analytical expressions for individual and joint optimal PA, RP, and PS are obtained by exploiting convexity of outage minimization problem for the no direct link case. In case of direct source-to-destination link, multipseudoconvexity of joint-optimal PA, RP, and PS problem is proved, and alternating optimization is used to find the global optimal solution. Numerical results show that the joint optimal solutions, although strongly influenced by the harvested power requirement at the destination, can provide respectively 64% and 100% outage improvement over the fixed allocation scheme for without and with direct link.

WATCLUST: a tool for improving the design of drugs based on protein-water interactions.

Water molecules are key players for protein folding and function. On the protein surface, water is not placed randomly, but display instead a particular structure evidenced by the presence of specific water sites (WS). These WS can be derived and characterized using explicit water Molecular Dynamics simulations, providing useful information for ligand binding prediction and design. Here we present WATCLUST, a WS determination and analysis tool running on the VMD platform. The tool also allows direct transfer of the WS information to Autodock program to perform biased docking. The WATCLUST plugin and documentation are freely available at http://sbg.qb.fcen.uba.ar/watclust/. marcelo@qi.fcen.uba.ar, adrian@qi.fcen.uba.ar.

Is the geomagnetic map imprinted in pre-emergent egg?

Although it is well-accepted that the geomagnetic field (GMF) plays an important role in animal navigation and migration, key problems remain unanswered. To explain the puzzling ability of hatchlings to embark on unexplored migrational journeys we hypothesize that mothers who have previously navigated the trip enable their offspring by direct transfer of route information to their eggs prior to hatching. The freshly hatched animal registers the local GMF as a reference point before embarking on the journey the mother has prepared for it. This process represents a novel type of biological cycle that finesses the need to treat questions such as natal homing and route parameters separately.

What will this do to me and my brain? Ethical issues in brain-to-brain interfacing.

Recent brain-to-brain interfacing studies provide proof of principle for the feasibility of various forms of direct information transfer between two brains, and may lead to the development of new approaches involving memory, emotions, or senses. What makes brain-to-brain interfaces unique is the transfer of information representing specific messages directly from one brain to another, without involving any activity of the peripheral nervous system or senses. The article discusses ethical issues that arise in neural interfacing. The focus is on the implications that brain-to-brain interfaces may have on the individual at the recipient side.

A protein complex containing Epo1p anchors the cortical endoplasmic reticulum to the yeast bud tip.

The cortical endoplasmic reticulum (cER) of yeast underlies the plasma membrane (PM) at specific contact sites to enable a direct transfer of information and material between both organelles. During budding, directed movement of cER to the young bud followed by subsequent anchorage at its tip ensures the faithful inheritance of this organelle. The ER membrane protein Scs2p tethers the cER to the PM and to the bud tip through so far unknown receptors. We characterize Epo1p as a novel member of the polarisome that interacts with Scs2p exclusively at the cell tip during bud growth and show that Epo1p binds simultaneously to the Cdc42p guanosine triphosphatase-activating protein Bem3p. Deletion of EPO1 or deletion of BEM3 in a polarisome-deficient strain reduces the amount of cER at the tip. This analysis therefore identifies Epo1p as a novel and important component of the polarisome that promotes cER tethering at sites of polarized growth.

Using phase shift Granger causality to measure directed connectivity in EEG recordings.

Cortical activity is maintained by neural networks working in tandem. Electroencephalographic (EEG) signals across two sites are said to be coherent with one another when they show consistent phase relations. However, periods of desynchrony beginning with a shift in phase relations are a necessary aspect of information processing. Traditional measures of EEG coherence lack the temporal resolution required to divide the relationship between two signals into periods of synchrony and desynchrony and are unable to specify the direction of information transmission (i.e., which site is leading and which is lagging), a goal referred to as directed connectivity. In this article, the authors introduce a novel method of measuring directed connectivity by applying the framework of Granger causality to phase shift events which are estimated with high temporal resolution. A simulation study is used to verify that the proposed method is able to identify connectivity patterns in situations similar to EEG recordings, such as high levels of noise and linear source mixing. Their method is able to correctly identify both the existence and direction of information transfer, and that the existence of spatiotemporal noise serves to reduce the spread of shift identification due to volume conduction. To demonstrate the method on real data, it is applied to EEG recordings from 18 adolescents during a resting period and auditory and visual vigilance tasks. Their new measure, Phase Shift Granger Causality (PSGC), is able to clearly distinguish between the resting task and the active tasks. The latter have higher rates of connectivity overall and specifically more long-range connections. As expected, the resting task appears to activate more localized neural circuitry, whereas the active tasks appear to increase communication across several neural regions involved in vigilance tasks. The vigilance tasks also showed significantly higher clustering coefficients than the resting task, a property associated with small-world networks.

The contribution of frequency-specific activity to hierarchical information processing in the human auditory cortex.

The fact that feed-forward and top-down propagation of sensory information use distinct frequency bands is an appealing assumption for which evidence remains scarce. Here we obtain human depth recordings from two auditory cortical regions in both hemispheres, while subjects listen to sentences, and show that information travels in each direction using separate frequency channels. Bottom-up and top-down propagation dominates in γ- and δ–β (<40 Hz) bands, respectively. The predominance of low frequencies for top-down information transfer is confirmed by cross-regional frequency coupling, which indicates that the power of γ-activity in A1 is modulated by the phase of δ–β activity sampled from association auditory cortex (AAC). This cross-regional coupling effect is absent in the opposite direction. Finally, we show that information transfer does not proceed continuously but by time windows where bottom-up or top-down processing alternatively dominates. These findings suggest that the brain uses both frequency- and time-division multiplexing to optimize directional information transfer.

Spatio-Temporal Changes in Potential Evaporation Based on Entropy Across the Wei River Basin

The distribution of potential evaporation is highly unstable due to complex human activities and climate changes. Therefore, it is of great significance for further understanding hydrological cycle to estimate potential evaporation distribution. Reasonable regionalization of potential evaporation will help to improve the efficiency of irrigation and increase the ability of drought relief, which is of great importance to irrigation planning and management. Hence, the spatio-temporal changes in potential evaporation distribution at monthly and annual scales are investigated based on the modified Mann-Kendall trend test method and the entropy theory in the Wei River Basin. A nonparametric method as an attractive alternative to empirical and parametric approaches is proposed to calculate the univariate and bivariate probability distribution of potential evaporation. The directional information transfer index (DITI) is employed to estimate the similarity among the meteorological stations, and the k-means cluster analysis is used to classify the meteorological stations into several distribution zones with distinct features. Based on the monthly potential evaporation from 1960 to 2008 at 21 meteorological stations, the basin is ultimately classified into 8 zones with their own distinct spatio-temporal distribution features. In view of the distinct spatio-temporal distribution features, the DITI-based model combined with the nonparametric probability estimation method and the k-means cluster analysis offers a more precise classification of potential evaporation distribution zones.

Transfer of directional information between the polarization compass and the sun compass in desert ants

Desert ants, Cataglyphis fortis, perform large foraging excursions during which they continuously compute a home vector that allows them to return to the nest on the shortest way. This type of navigation, termed path integration, needs a compass system and an odometer. Ants use several cues to determine their walking direction, two of the most important ones being the sun position and the polarization pattern of the sky. We tested whether an information transfer is possible from one compass system to the other, which depend on different anatomical substrates. Since the sky's polarization pattern is detected by UV-photoreceptors located in the dorsal rim area (DRA), we used an orange Perspex filter that eliminated the UV part of the spectrum to prevent the use of the polarization compass. The use of the sun compass could be excluded by appropriate screens. In the critical tests the ants had learned a nest-feeder direction with e.g. the sun compass only, and were later tested with the polarization compass, or vice versa. The results show that a transfer is possible in both directions.

Conceptual mappings and neural reuse.

TOO MUCH NEURAL REUSE, EVEN FOR A METAPHORICAL BRAIN Conceptual mappings are correspondances between conceptual domains (SPACE, TIME, FORCE, EMOTION, etc.) or between entities within the same conceptual domain. Through mapping, we project inferences, elements, and relations from one mental configuration to another. Sets of mappings can become entrenched, creating powerful cognitive habits. For example, across many cultures around the world, temporal relations are conceived by means of spatial relations, in language (“Saturday is almost here”), artifacts (timelines, calendars, sundials), or gesture (Nunez and Sweetser, 2006). Some of the mappings for this template are: duration is spatial extent, events are landmarks, or time is motion along a path. From over 30 years of conceptual mappings research emerges a picture of the conceptual system as a set of mapping habits. Instead of a static repository of concepts, we have a dynamic network connecting mental structures. Mapping is not exceptional: it is the norm. It is through mapping that concepts are formed, learned, and developed creatively. These ideas have boosted the interest in the most remarkable manifestations of mapping in language and thought: metaphor, metonymy, analogy, counterfactuals, etc. Metaphor has received far more attention than all the other phenomena combined. Researchers in Conceptual Metaphor Theory (CMT) (Lakoff and Johnson, 1980; Lakoff, 1993), have identified many sets of cross-domain mappings underlying conventional metaphorical expressions: TIME IS SPACE, LIFE IS A JOURNEY, ANGER IS HEAT, EVENTS ARE ACTIONS, etc. According to CMT, conceptual metaphors are static, ontological, fixed sets of partial correspondances between two conceptual domains. Metaphor transfers inferences from the source domain, more concrete or better structured, to the target domain, which is more abstract or less delineated. A system of thousands of metaphorical mappings constitutes the main mechanism for abstract thought in the human mind. From the nineties, the semantic postulates of CMT have been used to develop the Neural Theory of Language (NTL) (Gallese and Lakoff, 2005; Feldman, 2008; Lakoff, 2008). In NTL, conceptual metaphors are replaced by neural mappings, combinations of simple neural circuits that carry out conceptual mappings. The major function of all this neural binding is the reuse of sensorimotor brain mechanisms for new roles in language and reasoning. This is congenial with the grounding of abstract concepts in perceptual experience (Barsalou, 1999, 2008), called embodiment in conceptual mappings research (Johnson, 1987, 2008; Lakoff, 1987; Lakoff and Johnson, 1999). The overarching idea of CMT-NTL is a “metaphorical mind-brain,” based on direct, binary transfer across domains. The transfer is carried out through static cognitive habits, which are implemented by neural circuitry connecting pairs of brain areas. For the brain, metaphor is once more privileged over all other manifestations of mapping, just like it was for the mind. A good example of the rapidly growing interest in the neuroscience of metaphor is the Frontiers issue about the topic, currently being edited by Vicky T. Lai and Seana Coulson. But the metaphorical brain seems quite insufficient to account for the pervasiveness and complexity of neural reuse. In a recent BBS target article, Michael Anderson (2010) shows that what is going on in the brain dwarfs the predictions of embodiment or CMT-NTL. Statistics run on thousands of fMRI studies indicate that even fairly small brain regions are typically reused in multiple tasks, with even higher reuse probabilities if a region is involved in perception or action (Anderson et al., 2010). Neural reuse is ubiquitous and dynamic, and many of its results cannot be explained as domain-structuring inheritance. Anderson examines, among others, the following examples: the SNARC effect (a mental number line with magnitudes increasing from left to right), the correlation between finger representation and numerical cognition, the interaction of word and gesture, or the phonological loop in working memory. These cases present no metaphorical projection, and some of them involve more than two components. Rather than direct transfer of information, a given system seems to be reused for a non-primary purpose because it happens to have a function or structure that are appropriate for the particular cognitive task at hand. As Anderson claims, we need a broader theoretical framework, able to account for those individual phenomena as well as for the general prevalence of neural reuse.