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PubMed1995

Receptive field structure in the visual cortex: does selective stimulation induce plasticity?

Sensory areas of adult cerebral cortex can reorganize in response to long-term alterations in patterns of afferent signals. This long-term plasticity is thought to play a crucial role in recovery from injury and in some forms of learning. However, the degree to which sensory representations in primary cortical areas depend on short-term (i.e., minute to minute) stimulus variations remains unclear. A traditional view is that each neuron in the mature cortex has a fixed receptive field structure. An alternative view, with fundamentally different implications for understanding cortical function, is that each cell's receptive field is highly malleable, changing according to the recent history of the sensory environment. Consistent with the latter view, it has been reported that selective stimulation of regions surrounding the receptive field induces a dramatic short-term increase in receptive field size for neurons in the visual cortex [Pettet, M. W. & Gilbert, C. D. (1992) Proc. Natl. Acad. Sci. USA 89, 8366-8370]. In contrast, we report here that there is no change in either the size or the internal structure of the receptive field following several minutes of surround stimulation. However, for some cells, overall responsiveness increases. These results suggest that dynamic alterations of receptive field structure do not underlie short-term plasticity in the mature primary visual cortex. However, some degree of short-term adaptability could be mediated by changes in responsiveness.

Animals↗

PubMed1994

Influence of educational level of non brain-damaged subjects on visual naming capacities.

Educational level of subjects is a variable often neglected in neuropsychological studies. However, there are pieces of evidence to suggest that illiterate subjects may perform worse than literate subjects in some tests. Visual naming is one of the tasks where a poor performance was reported in illiterate populations. The present study addresses this problem of comparing the performance in visual naming tasks of non-brain-damaged patients of different educational levels. The test materials were composed of three subtests: naming real objects, their photographs, and line drawings of the same objects. Results revealed that there is a clear influence of educational level on the ability to name photographs and line drawings of the objects. Naming line drawings is particularly difficult for the lower educated non-brain-damaged subjects. Visual analysis of two dimensional representations is a task that requires special learning. These results have to be taken into consideration in test selection for poorly educated populations.

Aged↗

PubMedDate not supplied

How is the serial order of a verbal sequence coded? Some comparisons between models.

Current models of verbal short-term memory (STM) propose various mechanisms for serial order. These include a gradient of activation over items, associations between items, and associations between items and their positions relative to the start or end of a sequence. We compared models using a variant of Hebb's procedure in which immediate serial recall of a sequence improves if the sequence is presented more than once. However, instead of repeating a complete sequence, we repeated different aspects of serial order information common to training lists and a subsequent test list. In Experiment 1, training lists repeated all the item-item pairings in the test list, with or without the position-item pairings in the test list. Substantial learning relative to a control condition was observed only when training lists repeated item-item pairs with position-item pairs, and position was defined relative to the start rather than end of a sequence. Experiment 2 attempted to analyse the basis of this learning effect further by repeating fragments of the test list during training, where fragments consisted of either isolated position-item pairings or clusters of both position-item and item-item pairings. Repetition of sequence fragments led to only weak learning effects. However, where learning was observed it was for specific position-item pairings. We conclude that positional cues play an important role in the coding of serial order in memory but that the information required to learn a sequence goes beyond position-item associations. We suggest that whereas STM for a novel sequence is based on positional cues, learning a sequence involves the development of some additional representation of the sequence as a whole.

Adolescent↗

PubMed2025

Tomtom-lite: accelerating Tomtom enables large-scale and real-time motif similarity scoring.

SUMMARY: Pairwise sequence similarity is a core operation in genomic analysis, yet most attention has been given to sequences made up of discrete characters. With the growing prevalence of machine learning, calculating similarities for sequences of continuous representations, e.g. frequency-based position-weight matrices (PWMs) and attribution-based contribution-weight matrices, is taking on newfound importance. Tomtom has previously been proposed as an algorithm for identifying pairs of PWMs whose similarity is statistically significant, but the implementation remains inefficient for both real-time and large-scale analysis. Accordingly, we have re-implemented Tomtom as a numba-accelerated Python function that is natively multi-threaded, avoids cache misses, more efficiently caches intermediate values, and uses approximations at compute bottlenecks. Here, we provide a detailed description of the original Tomtom method and present results demonstrating that our re-implementation can achieve over a 1000-fold speedup compared with the original tool on reasonable tasks. AVAILABILITY AND IMPLEMENTATION: Our implementation of Tomtom is freely available as a Python package at https://github.com/jmschrei/memesuite-lite, which can be downloaded via pip install memelite or at https://zenodo.org/records/17008952.

Software↗

PubMed2026

A full review of online education resources available on antifungal stewardship.

BACKGROUND AND OBJECTIVES: Antifungal resistance represents an increasing global threat, driven by the rising burden of fungal disease. Antifungal stewardship (AFS) is a critical component of broader antimicrobial resistance (AMR) efforts, but education in this area remains less established than antibacterial stewardship initiatives. The scope and characteristics of the current landscape of online AFS resources have not yet been systematically described. To identify and evaluate online educational resources focused on fungal disease management and AFS, and assess their accessibility, format, educational design and implementation focus. METHODS: A structured search of internet search engines, distribution platforms and organizational websites was conducted to identify English-language web-based resources related to fungal disease management and stewardship. Resources were evaluated using predefined criteria including access model, format, length, educational design, interactivity and AFS content. An overall educational value score (1-10) was assigned. RESULTS: Twenty-three educational resources were identified. Most were delivered as online unfacilitated courses (11, 48%) and were short (<4 h) (12, 52%). Most focused on guidelines and syndromic management (18, 78%) and targeted doctors and/or nurses/midwives (22, 96%). Limited interactivity was reported in nine (39%) courses. Five courses (22%) had either a substantial or comprehensive focus on AFS. CONCLUSIONS: Online AFS educational resources are available and support awareness and knowledge development. However, they remain relatively few in number. Greater emphasis on implementation-focused learning, behaviour change components and broader global representation may enhance their impact.

Journal Article↗

PubMed2000

Cooperative coevolution of neural representations.

A genetic algorithm (GA) is used to search for a set of local feature detectors or hidden units. These are in turn employed as a representation of the input data for neural learning in the upper layer of a multilayer perceptron (MLP) which performs an image classification task. Three different methods of encoding hidden unit weights in the chromosome of the GA are presented, including one which coevolves all the feature detectors in a single chromosome, and two which promote the cooperation of feature detectors by encoding them in their own individual chromosomes. The fitness function measures the MLP classification accuracy together with the confidence of the networks.

Algorithms↗

PubMed2005

Event based self-supervised temporal integration for multimodal sensor data.

A method for synergistic integration of multimodal sensor data is proposed in this paper. This method is based on two aspects of the integration process: (1) achieving synergistic integration of two or more sensory modalities, and (2) fusing the various information streams at particular moments during processing. Inspired by psychophysical experiments, we propose a self-supervised learning method for achieving synergy with combined representations. Evidence from temporal registration and binding experiments indicates that different cues are processed individually at specific time intervals. Therefore, an event-based temporal co-occurrence principle is proposed for the integration process. This integration method was applied to a mobile robot exploring unfamiliar environments. Simulations showed that integration enhanced route recognition with many perceptual similarities; moreover, they indicate that a perceptual hierarchy of knowledge about instant movement contributes significantly to short-term navigation, but that visual perceptions have bigger impact over longer intervals.

Animals↗

PubMed2000

Selective use of perceptual recalibration versus visuomotor skill acquisition.

Exposure to laterally displacing prisms is characterized by systematic misreaching in the opposite direction after prisms are removed. Other learning tasks involving altered visuomotor mappings can often be mastered by the subject with minimal resulting aftereffects. One variable that may account for this difference is the nature of the feedback provided to the subject: during studies of prism exposure, subjects usually view the hand itself, whereas in many studies of visuomotor learning, subjects view a computer-generated representation of the hand position or movement. We compared the use of actual feedback of the hand with computer-generated representational feedback of its position during exposure to laterally displacing prisms. In the actual feedback condition (ACT), a light on the fingertip was illuminated immediately at the end of each reach. In the representational feedback condition (REP), a computer-generated spot of light was displayed to indicate the exact position of the fingertip at the end of each reach. Whereas the rate and magnitude of error correction were the same in both conditions, only the ACT condition produced the large adaptive aftereffect typically observed after prism exposure. These results suggest that the perception of a physical coincidence between the feedback source and the hand may be a key factor in determining whether adaptation is accomplished through perceptual recalibration or visuomotor skill acquisition.

Adaptation, Physiological↗

PubMed2005

On the nonlearnability of a single spiking neuron.

We study the computational complexity of training a single spiking neuron N with binary coded inputs and output that, in addition to adaptive weights and a threshold, has adjustable synaptic delays. A synchronization technique is introduced so that the results concerning the nonlearnability of spiking neurons with binary delays are generalized to arbitrary real-valued delays. In particular, the consistency problem for N with programmable weights, a threshold, and delays, and its approximation version are proven to be NP-complete. It follows that the spiking neurons with arbitrary synaptic delays are not properly PAC learnable and do not allow robust learning unless RP = NP. In addition, the representation problem for N, a question whether an n-variable Boolean function given in DNF (or as a disjunction of O(n) threshold gates) can be computed by a spiking neuron, is shown to be coNP-hard.

Action Potentials↗

PubMedDate not supplied

[Teaching development and professional identity in nursing: the system of concepts as a mediator in learning].

The focus of this study is characterisation of the representations socially constituted about the concepts "Nursing" and "Nursing and context". The interpretative mental schemes were sequentially configured during the Graduation course starting from the written answers supplied by students to the following questions: "How do you judge Nursing?" and "What is the relation between the profession and social context? "We have used interpretation schemes based on the contain analysis. As a result, we have identified a peculiar development of schemes formed by means of structures that were involved with forming system and used system of human resources as reference which promote distinct perspectives of professional performance. The components nucleuses of each stage of conception expressed the logical structure which were incorporated to subsequent construction, that configures a evolution determined by selective adhesion of students to the graduation or to the practice field. There has been a movement alongside to those systems resulting from discrepancy between the experience and personal schemes.

Education, Nursing, Baccalaureate↗

PubMed1995

Teaching of human anatomy: a role for computer animation.

Computer-assisted learning fulfils an important need for pictorial representation of the functions of organs and systems. The various computer techniques of animation and morphing provide promising horizons for medical educational technology. Image acquisition is one of the most resource-intensive components of animation sequence development. Images can be drawn as originals or can be copied/scanned from various sources. By standardizing the initial (starting) image to the particular/basic need of the teacher and projecting the end-point image by using a vector animation package, 'films' can be created to demonstrate any form of movement. In the Anatomy Department, Sultan Qaboos University in Muscat, computer-animated tutorials are being introduced to illustrate normal and abnormal functional anatomy. The heart and its valve mechanisms have been selected as a pilot study. The student response is very positive and the technique has great potential. Embryology animations showing the formation and growth of organs such as the brain and spinal cord are also being developed.

Anatomy↗

PubMed2003

Simultaneous spatial updating in nested environments.

When one moves, the spatial relationship between oneself and the entire world changes. Spatial updating refers to the cognitive process that computes these relationships as one moves. In two experiments, we tested whether spatial updating occurs automatically for multiple environments simultaneously. Participants turned relative to either a room or the surrounding campus buildings and then pointed to targets in both the environment in which they turned (updated environment) and the other environment (nonupdated environment). The participants automatically updated the room targets when they moved relative to the campus, but they did not update the campus targets when they moved relative to the room. Thus, automatic spatial updating depends on the nature of the environment. Implications for theories of spatial learning and the structure of human spatial representations are discussed.

Attention↗

PubMed2001

What makes catchment management groups "tick"?

The work of catchment management groups throughout Australia represents a significant economic and social investment in natural resource management. Institutional structures and policies, the role of on-ground coordinators, facilitation processes, citizen participation and social capital are critical factors influencing the success of catchment management groups. From a participant-researcher viewpoint, this paper signposts research directions and themes that are being pursued from the participant/coordinator, catchment group, and lead government/non-government agency perspective on the influence of these factors on the success of a catchment management group in the Pumicestone Region of Southeast Queensland, Australia. Research directions, themes and discussion/reflection points for practitioners include--the importance of understanding milieu; motivation; success; having fun; "networking networks"; involvement of "nontraditional" stakeholders; development of stakeholder/participant partnerships; learning from other practitioners; methods of stakeholder/participant representation; evaluation; the need for guiding principles or philosophy; the equivalence of planning, implementation, evaluation, and resourcing; catchments as fundamental units of Nature; continuity of support for groups; recognising a new role for government; working with existing networks; and the need for an eclectic approach to natural resource management.

Community-Institutional Relations↗

PubMed2006

Generalism versus subspecialization: changes necessary in medical education.

During the initial Partners Meeting of the Association of Faculties of Medicine of Canada (AFMC), the Canadian Association for Medical Education (CAME), the College of Family Physicians of Canada (CFPC), the Medical Council of Canada (MCC), and the Royal College of Physicians and Surgeons of Canada (RCPSC) in May 2005, a plenary discussion and debate focused on the tensions that exist between generalist and subspecialty education within both the undergraduate and postgraduate educational programs in Canadian medical schools. Key issues identified in the debate included medical student selection, generalist representation on medical school faculty and in learning experiences, and the need for a greater teaching role and respect for generalism to be developed.

Canada↗

PubMed1997

Optimal, unsupervised learning in invariant object recognition.

A means for establishing transformation-invariant representations of objects is proposed and analyzed, in which different views are associated on the basis of the temporal order of the presentation of these views, as well as their spatial similarity. Assuming knowledge of the distribution of presentation times, an optimal linear learning rule is derived. Simulations of a competitive network trained on a character recognition task are then used t highlight the success of this learning rule in relation to simple Hebbian learning and to show that the theory can give accurate quantitative predictions for the optimal parameters for such networks.

Animals↗

PubMed2003

Learning higher-order structures in natural images.

The theoretical principles that underlie the representation and computation of higher-order structure in natural images are poorly understood. Recently, there has been considerable interest in using information theoretic techniques, such as independent component analysis, to derive representations for natural images that are optimal in the sense of coding efficiency. Although these approaches have been successful in explaining properties of neural representations in the early visual pathway and visual cortex, because they are based on a linear model, the types of image structure that can be represented are very limited. Here, we present a hierarchical probabilistic model for learning higher-order statistical regularities in natural images. This non-linear model learns an efficient code that describes variations in the underlying probabilistic density. When applied to natural images the algorithm yields coarse-coded, sparse-distributed representations of abstract image properties such as object location, scale and texture. This model offers a novel description of higher-order image structure and could provide theoretical insight into the response properties and computational functions of lower level cortical visual areas.

Learning↗

PubMed2004

Excitotoxic lesions of the medial striatum delay extinction of a reinforcement color discrimination operant task in domestic chicks; a functional role of reward anticipation.

To reveal the functional roles of the striatum, we examined the effects of excitotoxic lesions to the bilateral medial striatum (mSt) and nucleus accumbens (Ac) in a food reinforcement color discrimination operant task. With a food reward as reinforcement, 1-week-old domestic chicks were trained to peck selectively at red and yellow beads (S+) and not to peck at a blue bead (S-). Those chicks then received either lesions or sham operations and were tested in extinction training sessions, during which yellow turned out to be nonrewarding (S-), whereas red and blue remained unchanged. To further examine the effects on postoperant noninstrumental aspects of behavior, we also measured the "waiting time", during which chicks stayed at the empty feeder after pecking at yellow. Although the lesioned chicks showed significantly higher error rates in the nonrewarding yellow trials, their postoperant waiting time gradually decreased similarly to the sham controls. Furthermore, the lesioned chicks waited significantly longer than the controls, even from the first extinction block. In the blue trials, both lesioned and sham chicks consistently refrained from pecking, indicating that the delayed extinction was not due to a general disinhibition of pecking. Similarly, no effects were found in the novel training sessions, suggesting that the lesions had selective effects on the extinction of a learned operant. These results suggest that a neural representation of memory-based reward anticipation in the mSt/Ac could contribute to the anticipation error required for extinction.

Analysis of Variance↗

PubMed1999

Pre-synaptic lateral inhibition provides a better architecture for self-organizing neural networks.

Unsupervised learning is an important ability of the brain and of many artificial neural networks. A large variety of unsupervised learning algorithms have been proposed. This paper takes a different approach in considering the architecture of the neural network rather than the learning algorithm. It is shown that a self-organizing neural network architecture using pre-synaptic lateral inhibition enables a single learning algorithm to find distributed, local, and topological representations as appropriate to the structure of the input data received. It is argued that such an architecture not only has computational advantages but is a better model of cortical self-organization.

Algorithms↗