Human intelligence comprises comprehension of and reasoning about an infinitely variable external environment. A brain capable of large variability in neural configurations, or states, will more easily understand and predict variable external events. Entropy measures the variety of configurations possible within a system, and recently the concept of brain entropy has been defined as the number of neural states a given brain can access. This study investigates the relationship between human intelligence and brain entropy, to determine whether neural variability as reflected in neuroimaging signals carries information about intellectual ability. We hypothesize that intelligence will be positively associated with entropy in a sample of 892 healthy adults, using resting-state fMRI. Intelligence is measured with the Shipley Vocabulary and WASI Matrix Reasoning tests. Brain entropy was positively associated with intelligence. This relation was most strongly observed in the prefrontal cortex, inferior temporal lobes, and cerebellum. This relationship between high brain entropy and high intelligence indicates an essential role for entropy in brain functioning. It demonstrates that access to variable neural states predicts complex behavioral performance, and specifically shows that entropy derived from neuroimaging signals at rest carries information about intellectual capacity. Future work in this area may elucidate the links between brain entropy in both resting and active states and various forms of intelligence. This insight has the potential to provide predictive information about adaptive behavior and to delineate the subdivisions and nature of intelligence based on entropic patterns.
Problem solving and innovation are key components of intelligence. We compare wild-caught individuals from two species that are close relatives of Darwin’s finches, the innovativeLoxigilla barbadensis, and its most closely related species in Barbados, the conservativeTiaris bicolor. We found an all-or-none difference in the problem-solving capacity of the two species. Brain RNA sequencing analyses revealed interspecific differences in genes related to neuronal and synaptic plasticity in the intrapallial neural populations (mesopallium and nidopallium), especially in the nidopallium caudolaterale, a structure functionally analogous to the mammalian prefrontal cortex. At a finer scale, we discovered robust differences in glutamate receptor expression between the species. In particular, the GRIN2B/GRIN2A ratio, known to correlate with synaptic plasticity, was higher in the innovativeL. barbadensis. These findings suggest that divergence in avian intelligence is associated with similar neuronal mechanisms to that of mammals, including humans.
- Proceedings of the National Academy of Sciences of the United States of America
- Published almost 4 years ago
Deep networks are now able to achieve human-level performance on a broad spectrum of recognition tasks. Independently, neuromorphic computing has now demonstrated unprecedented energy-efficiency through a new chip architecture based on spiking neurons, low precision synapses, and a scalable communication network. Here, we demonstrate that neuromorphic computing, despite its novel architectural primitives, can implement deep convolution networks that (i) approach state-of-the-art classification accuracy across eight standard datasets encompassing vision and speech, (ii) perform inference while preserving the hardware’s underlying energy-efficiency and high throughput, running on the aforementioned datasets at between 1,200 and 2,600 frames/s and using between 25 and 275 mW (effectively >6,000 frames/s per Watt), and (iii) can be specified and trained using backpropagation with the same ease-of-use as contemporary deep learning. This approach allows the algorithmic power of deep learning to be merged with the efficiency of neuromorphic processors, bringing the promise of embedded, intelligent, brain-inspired computing one step closer.
Numerous authors reported a prevalence of perfectionism in gifted populations. In addition, an unhealthy form of perfectionism that leads to anxiety disorder has been described. Using self-report measures (CAPS and R-CMAS) with 132 children, we hypothesized that intellectually gifted children express a higher level of perfectionism and anxiety. Our results pointed out a paradox: the gifted group obtained a higher self-oriented perfectionism score than the control group in 6th grade, but present the same level of anxiety. In contrast, the gifted group showed the same level of perfectionism than non-gifted 5(th) graders, but reported a higher anxiety level. Thus, the interplay between perfectionism and anxiety appears to be more complex than a simple linear relationship in giftedness.
We present a behavioural task designed for the investigation of how novel instrumental actions are discovered and learnt. The task consists of free movement with a manipulandum, during which the full range of possible movements can be explored by the participant and recorded. A subset of these movements, the ‘target’, is set to trigger a reinforcing signal. The task is to discover what movements of the manipulandum evoke the reinforcement signal. Targets can be defined in spatial, temporal, or kinematic terms, can be a combination of these aspects, or can represent the concatenation of actions into a larger gesture. The task allows the study of how the specific elements of behaviour which cause the reinforcing signal are identified, refined and stored by the participant. The task provides a paradigm where the exploratory motive drives learning and as such we view it as in the tradition of Thorndike . Most importantly it allows for repeated measures, since when a novel action is acquired the criterion for triggering reinforcement can be changed requiring a new action to be discovered. Here, we present data using both humans and rats as subjects, showing that our task is easily scalable in difficulty, adaptable across species, and produces a rich set of behavioural measures offering new and valuable insight into the action learning process.
IN A SEMINAL PAPER WRITTEN FIVE DECADES AGO, CRONBACH DISCUSSED THE TWO HIGHLY DISTINCT APPROACHES TO SCIENTIFIC PSYCHOLOGY: experimental and correlational. Today, although these two approaches are fruitfully implemented and embraced across some fields of psychology, this synergy is largely absent from other areas, such as in the study of learning and behavior. Both Tolman and Hull, in a rare case of agreement, stated that the correlational approach held little promise for the understanding of behavior. Interestingly, this dismissal of the study of individual differences was absent in the biologically oriented branches of behavior analysis, namely, behavioral genetics and ethology. Here we propose that the distinction between “causation” and “causes of variation” (with its origins in the field of genetics) reveals the potential value of the correlational approach in understanding the full complexity of learning and behavior. Although the experimental approach can illuminate the causal variables that modulate learning, the analysis of individual differences can elucidate how much and in which way variables interact to support variations in learning in complex natural environments. For example, understanding that a past experience with a stimulus influences its “associability” provides little insight into how individual predispositions interact to modulate this influence on associability. In this “new” light, we discuss examples from studies of individual differences in animals' performance in the Morris water maze and from our own work on individual differences in general intelligence in mice. These studies illustrate that, opposed to what Underwood famously suggested, studies of individual differences can do much more to psychology than merely providing preliminary indications of cause-effect relationships.
INTRODUCTION: The Borderline Intellectual Functioning (BIF) is conceptualized as the frontier that delimits “normal” intellectual functioning from intellectual disability (IQ 71-85). In spite of its magnitude, its prevalence cannot be quantified and its diagnosis has not yet been defined. OBJECTIVES: To elaborate a conceptual framework and to establish consensus guidelines. METHOD: A mixed qualitative methodology, including frame analysis and nominal groups techniques, was used. The literature was extensively reviewed in evidence based medical databases, scientific publications, and the grey literature. This information was studied and a framing document was prepared. RESULTS: Scientific publications covering BIF are scarce. The term that yields a bigger number of results is “Borderline Intelligence”. The Working Group detected a number of areas in which consensus was needed and wrote a consensus document covering the conclusions of the experts and the framing document. CONCLUSIONS: It is a priority to reach an international consensus about the BIF construct and its operative criteria, as well as to develop specific tools for screening and diagnosis. It is also necessary to define criteria that enable its incidence and prevalence. To know what interventions are the most efficient, and what are the needs of this population, is vital to implement an integral model of care centred on the individual.
Skilled performers such as athletes or musicians can improve their performance by imagining the actions or sensory outcomes associated with their skill. Performers vary widely in their auditory and motor imagery abilities, and these individual differences influence sensorimotor learning. It is unknown whether imagery abilities influence both memory encoding and retrieval. We examined how auditory and motor imagery abilities influence musicians' encoding (during Learning, as they practiced novel melodies), and retrieval (during Recall of those melodies). Pianists learned melodies by listening without performing (auditory learning) or performing without sound (motor learning); following Learning, pianists performed the melodies from memory with auditory feedback (Recall). During either Learning (Experiment 1) or Recall (Experiment 2), pianists experienced either auditory interference, motor interference, or no interference. Pitch accuracy (percentage of correct pitches produced) and temporal regularity (variability of quarter-note interonset intervals) were measured at Recall. Independent tests measured auditory and motor imagery skills. Pianists' pitch accuracy was higher following auditory learning than following motor learning and lower in motor interference conditions (Experiments 1 and 2). Both auditory and motor imagery skills improved pitch accuracy overall. Auditory imagery skills modulated pitch accuracy encoding (Experiment 1): Higher auditory imagery skill corresponded to higher pitch accuracy following auditory learning with auditory or motor interference, and following motor learning with motor or no interference. These findings suggest that auditory imagery abilities decrease vulnerability to interference and compensate for missing auditory feedback at encoding. Auditory imagery skills also influenced temporal regularity at retrieval (Experiment 2): Higher auditory imagery skill predicted greater temporal regularity during Recall in the presence of auditory interference. Motor imagery aided pitch accuracy overall when interference conditions were manipulated at encoding (Experiment 1) but not at retrieval (Experiment 2). Thus, skilled performers' imagery abilities had distinct influences on encoding and retrieval of musical sequences.
The general consensus among sport and exercise genetics researchers is that genetic tests have no role to play in talent identification or the individualised prescription of training to maximise performance. Despite the lack of evidence, recent years have witnessed the rise of an emerging market of direct-to-consumer marketing (DTC) tests that claim to be able to identify children’s athletic talents. Targeted consumers include mainly coaches and parents. There is concern among the scientific community that the current level of knowledge is being misrepresented for commercial purposes. There remains a lack of universally accepted guidelines and legislation for DTC testing in relation to all forms of genetic testing and not just for talent identification. There is concern over the lack of clarity of information over which specific genes or variants are being tested and the almost universal lack of appropriate genetic counselling for the interpretation of the genetic data to consumers. Furthermore independent studies have identified issues relating to quality control by DTC laboratories with different results being reported from samples from the same individual. Consequently, in the current state of knowledge, no child or young athlete should be exposed to DTC genetic testing to define or alter training or for talent identification aimed at selecting gifted children or adolescents. Large scale collaborative projects, may help to develop a stronger scientific foundation on these issues in the future.
Little is known about why people differ in their levels of academic motivation. This study explored the etiology of individual differences in enjoyment and self-perceived ability for several school subjects in nearly 13,000 twins aged 9-16 from 6 countries. The results showed a striking consistency across ages, school subjects, and cultures. Contrary to common belief, enjoyment of learning and children’s perceptions of their competence were no less heritable than cognitive ability. Genetic factors explained approximately 40% of the variance and all of the observed twins' similarity in academic motivation. Shared environmental factors, such as home or classroom, did not contribute to the twin’s similarity in academic motivation. Environmental influences stemmed entirely from individual specific experiences.