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PubMed2001

Three learning phases for radial-basis-function networks.

In this paper, learning algorithms for radial basis function (RBF) networks are discussed. Whereas multilayer perceptrons (MLP) are typically trained with backpropagation algorithms, starting the training procedure with a random initialization of the MLP's parameters, an RBF network may be trained in many different ways. We categorize these RBF training methods into one-, two-, and three-phase learning schemes. Two-phase RBF learning is a very common learning scheme. The two layers of an RBF network are learnt separately; first the RBF layer is trained, including the adaptation of centers and scaling parameters, and then the weights of the output layer are adapted. RBF centers may be trained by clustering, vector quantization and classification tree algorithms, and the output layer by supervised learning (through gradient descent or pseudo inverse solution). Results from numerical experiments of RBF classifiers trained by two-phase learning are presented in three completely different pattern recognition applications: (a) the classification of 3D visual objects; (b) the recognition hand-written digits (2D objects); and (c) the categorization of high-resolution electrocardiograms given as a time series (ID objects) and as a set of features extracted from these time series. In these applications, it can be observed that the performance of RBF classifiers trained with two-phase learning can be improved through a third backpropagation-like training phase of the RBF network, adapting the whole set of parameters (RBF centers, scaling parameters, and output layer weights) simultaneously. This, we call three-phase learning in RBF networks. A practical advantage of two- and three-phase learning in RBF networks is the possibility to use unlabeled training data for the first training phase. Support vector (SV) learning in RBF networks is a different learning approach. SV learning can be considered, in this context of learning, as a special type of one-phase learning, where only the output layer weights of the RBF network are calculated, and the RBF centers are restricted to be a subset of the training data. Numerical experiments with several classifier schemes including k-nearest-neighbor, learning vector quantization and RBF classifiers trained through two-phase, three-phase and support vector learning are given. The performance of the RBF classifiers trained through SV learning and three-phase learning are superior to the results of two-phase learning, but SV learning often leads to complex network structures, since the number of support vectors is not a small fraction of the total number of data points.

Algorithms↗
PubMed2002

Learning of sequences of finger movements and timing: frontal lobe and action-oriented representation.

Motor sequence learning involves learning of a sequence of effectors with which to execute a series of movements and learning of a sequence of timings at which to execute the movements. In this study, we have segregated the neural correlates of the two learning mechanisms. Moreover, we have found an interaction between the two learning mechanisms in the frontal areas, which we claim as suggesting action-oriented coding in the frontal lobe. We used positron emission tomography and compared three learning conditions with a visuo-motor control condition. In two learning conditions, the subjects learned either a sequence of finger movements with random timing or a sequence of timing with random use of fingers. In the third condition the subjects learned to execute a sequence of specific finger movements at specific timing; we argue that it was only in this condition that the motor sequence was coded as an action-oriented representation. By looking for condition by session interactions (learning vs. control conditions over sessions), we have removed nonspecific time effects and identified areas that showed a learning-related increment of activation during learning. Learning of a finger sequence was associated with an increment of activation in the right intraparietal sulcus region and medial parietal cortex, whereas learning of a timing sequence was associated with an increment of activation in the lateral cerebellum, suggesting separate mechanisms for learning effector and temporal sequences. The left intraparietal sulcus region showed an increment of activation in learning of both finger and timing sequences, suggesting an overlap between the two learning mechanisms. We also found that the mid-dorsolateral prefrontal cortex, together with the medial and lateral premotor areas, became increasingly active when subjects learned a sequence that specified both fingers and timing, that is, when subjects were able to prepare specific motor action. These areas were not active when subjects learned a sequence that specified fingers or timing alone, that is, when subjects were still dependent on external stimuli as to the timing or fingers with which to execute the movements. Frontal areas may integrate the effector and temporal information of a motor sequence and implement an action-oriented representation so as to perform a motor sequence accurately and quickly. We also found that the mid-dorsolateral prefrontal cortex was distinguished from the ventrolateral prefrontal cortex and anterior fronto-polar cortex, which showed sustained activity throughout learning sessions and did not show either an increment or decrement of activation.

Adult↗
PubMed2002

Age-related biophysical alterations of hippocampal pyramidal neurons: implications for learning and memory.

Normal brain aging is associated with deficits in learning and memory. The hippocampus, a structure critical for proper learning and memory functions, is frequently implicated in aging-related learning deficits. There are many reports of learning-related changes in hippocampal pyramidal neurons from animals that were trained in hippocampus-dependent learning paradigms. One consistent finding in hippocampal pyramidal neurons is a learning-related increase in postsynaptic neuronal excitability, resulting from a reduction in the postburst afterhyperpolarization (AHP). The hippocampus, as well as the ability to acquire hippocampus-dependent tasks, is particularly affected by aging. Correspondingly, hippocampal neurons also display an age-related decrease in excitability, resulting from an enhanced AHP. The correlation between neuronal excitability and learning ability strongly suggests that changes in the AHP are critically involved in learning and age-related learning deficits. Additional support for this argument comes from in vitro studies that examined the effect of compounds that facilitated learning in aging animals on the properties of CA1 pyramidal neurons. Many of these compounds increased the excitability of CA1 pyramidal neurons by reducing the AHP. Subsequent voltage-clamp recordings showed that AHP reduction by these compounds mainly reflects the reduction of two of its currents, the I(AHP) and the sI(AHP). Conversely, age-related AHP enhancements primarily impact the I(AHP) and the sI(AHP). Given that the I(AHP) accounts for a small portion of the total AHP, and that the sI(AHP) is the AHP current that most critically modulates neuronal excitability, changes in neuronal excitability seen in learning and in aging are predominantly caused by changes in the sI(AHP). The fact that the sI(AHP) receives neuromodulation from many transmitter systems important for learning and sensitive to aging lends further support for its role in age-related learning deficits. In this article, we review: (1) two hippocampus-dependent learning tasks, trace eyeblink conditioning and Morris water maze training, that are used extensively in our laboratory to examine learning and aging-related learning deficits; (2) aging-related changes in several important neurotransmitter systems, and how the these changes impact learning and memory functions during aging; and (3) changes in the AHP and the sI(AHP) in hippocampal pyramidal neurons in relation to compromised neurotransmission, as well as to learning, in aging animals. The correlations between a reduction in the sI(AHP) in learning, and an enhancement in the sI(AHP) in aging provide compelling evidence that this current plays a critical role in cognitive functions, and further suggest that the key modulators of the AHP are good candidates for future therapeutic interventions in age-related neurodegenerative diseases.

Aging↗
PubMed2000

Changes in the responses of Purkinje cells in the floccular complex of monkeys after motor learning in smooth pursuit eye movements.

We followed simple- and complex-spike firing of Purkinje cells (PCs) in the floccular complex of the cerebellum through learned modifications of the pursuit eye movements of two monkeys. Learning was induced by double steps of target speed in which initially stationary targets move at a "learning" speed for 100 ms and then change to either a higher or lower speed in the same direction. In randomly interleaved control trials, targets moved at the learning speed in the opposite direction. When the learning direction was the ON direction for simple-spike responses, learning was associated with statistically significant changes in simple-spike firing for 10 of 32 PCs. Of the 10 PCs that showed significant expressions of learning, 8 showed changes in simple-spike output in the expected direction: increased or decreased firing when eye acceleration increased or decreased through learning. There were no statistically significant changes in simple-spike responses or eye acceleration during pursuit in the control direction. When the learning direction was in the OFF direction for simple-spike responses, none of 15 PCs showed significant correlates of learning. Although changes in simple-spike firing were recorded in only a subset of PCs, analysis of the population response showed that the same relationship between population firing and eye acceleration obtained before and after learning. Thus learning is associated with changes that render the modified population response appropriate to drive the changed behavior. To analyze complex-spike firing during learning we correlated complex-spike firing in the second, third, and fourth 100 ms after the onset of target motion with the retinal image motion in the previous 100 ms. Data were largely consistent with previous evidence that image motion drives complex spikes with a direction selectivity opposite that for simple spikes. Comparison of complex-spike responses at different times after the onset of control and learning target motions in the learning direction implied that complex spikes could guide learning during decreases but not increases in eye acceleration. Learning caused increases or decreases in the sensitivity of complex spikes to image motion in parallel with changes in eye acceleration. Complex-spike responses were similar in all PCs, including many in which learning did not modify simple-spike responses. Our data do not disprove current theories of cerebellar learning but suggest that these theories would have to be modified to account for simple- and complex-spike firing of floccular Purkinje cells reported here.

Action Potentials↗
PubMed2004

Dynamic analysis of learning in behavioral experiments.

Understanding how an animal's ability to learn relates to neural activity or is altered by lesions, different attentional states, pharmacological interventions, or genetic manipulations are central questions in neuroscience. Although learning is a dynamic process, current analyses do not use dynamic estimation methods, require many trials across many animals to establish the occurrence of learning, and provide no consensus as how best to identify when learning has occurred. We develop a state-space model paradigm to characterize learning as the probability of a correct response as a function of trial number (learning curve). We compute the learning curve and its confidence intervals using a state-space smoothing algorithm and define the learning trial as the first trial on which there is reasonable certainty (>0.95) that a subject performs better than chance for the balance of the experiment. For a range of simulated learning experiments, the smoothing algorithm estimated learning curves with smaller mean integrated squared error and identified the learning trials with greater reliability than commonly used methods. The smoothing algorithm tracked easily the rapid learning of a monkey during a single session of an association learning experiment and identified learning 2 to 4 d earlier than accepted criteria for a rat in a 47 d procedural learning experiment. Our state-space paradigm estimates learning curves for single animals, gives a precise definition of learning, and suggests a coherent statistical framework for the design and analysis of learning experiments that could reduce the number of animals and trials per animal that these studies require.

Algorithms↗
PubMed2005

Optometry and WebCT: a student survey of the value of web-based learning environments in optometric education.

PURPOSE: Improvements in information and communication technology and the need for off-campus delivery have led to the increased use of web-based learning tools in optometry schools around the world. This study compared student-reported preferences for traditional lecture-based learning with their preferences when using a web-based learning tool. METHODS: One hundred and thirteen second and third year students from the School of Optometry and Vision Science at the University of New South Wales were surveyed. All students had worked with WebCT for at least two years. Students were asked to rank a range of learning tools in perceived usefulness and also to state how often they used the particular learning tools. RESULTS: The students rated notes (lecture or WebCT delivered) and clinical laboratory sessions as their most useful learning tools. The use of specific learning tools was more diverse, with students reporting that they often used notes (lecture or WebCT delivered), the WebCT calendar tool and the WebCT discussion tool. This result highlights the valuable contribution of the communication aspect of WebCT to fostering learning communities. The least used learning tools were textbooks, websites mentioned in lectures and library print resources. Interestingly, the purchase of textbooks was high with 77 per cent of students on average reporting they had bought the recommended textbooks. CONCLUSION: Notes were the preferred learning tool of the optometry students at UNSW, suggesting that passive learning of content was the preferred learning style. It is hoped that the introduction of web-based learning environments may allow students and staff to reflect on their preferred teaching and learning styles. Web-based learning tools, such as WebCT, provide a powerful method to facilitate independent deeper learning in students with active learning styles. The current encouragement of student-based active learning methods should see increased use of independent learning platforms, such as WebCT, in optometry schools.

Computer-Assisted Instruction↗
PubMed2006

Visuomotor learning in immersive 3D virtual reality in Parkinson's disease and in aging.

Successful adaptation to novel sensorimotor contexts critically depends on efficient sensory processing and integration mechanisms, particularly those required to combine visual and proprioceptive inputs. If the basal ganglia are a critical part of specialized circuits that adapt motor behavior to new sensorimotor contexts, then patients who are suffering from basal ganglia dysfunction, as in Parkinson's disease should show sensorimotor learning impairments. However, this issue has been under-explored. We tested the ability of 8 patients with Parkinson's disease (PD), off medication, ten healthy elderly subjects and ten healthy young adults to reach to a remembered 3D location presented in an immersive virtual environment. A multi-phase learning paradigm was used having four conditions: baseline, initial learning, reversal learning and aftereffect. In initial learning, the computer altered the position of a simulated arm endpoint used for movement feedback by shifting its apparent location diagonally, requiring thereby both horizontal and vertical compensations. This visual distortion forced subjects to learn new coordinations between what they saw in the virtual environment and the actual position of their limbs, which they had to derive from proprioceptive information (or efference copy). In reversal learning, the sign of the distortion was reversed. Both elderly subjects and PD patients showed learning phase-dependent difficulties. First, elderly controls were slower than young subjects when learning both dimensions of the initial biaxial discordance. However, their performance improved during reversal learning and as a result elderly and young controls showed similar adaptation rates during reversal learning. Second, in striking contrast to healthy elderly subjects, PD patients were more profoundly impaired during the reversal phase of learning. PD patients were able to learn the initial biaxial discordance but were on average slower than age-matched controls in adapting to the horizontal component of the biaxial discordance. More importantly, when the biaxial discordance was reversed, PD patients were unable to make appropriate movement corrections. Therefore, they showed significantly degraded learning indices relative to age-matched controls for both dimensions of the biaxial discordance. Together, these results suggest that the ability to adapt to a sudden biaxial visuomotor discordance applied in three-dimensional space declines in normal aging and Parkinson disease. Furthermore, the presence of learning rate differences in the PD patients relative to age-matched controls supports an important contribution of basal ganglia-related circuits in learning novel visuomotor coordinations, particularly those in which subjects must learn to adapt to sensorimotor contingencies that were reversed from those just learned.

Adaptation, Physiological↗
PubMed2003

Problem-based learning in online vs. face-to-face environments.

UNLABELLED: This study compared outcomes of problem-based learning between synchronous online groups and face-to-face tutorial groups. Specifically, the study compared learning outcomes, time-on-task and learning issue generation. METHODS AND PROCEDURES: A post-test only control group design was used to investigate the effects of learning conditions on learning outcomes and processes. The experimental learning condition was defined as computer-mediated problem-based learning (CMPBL) and the control condition was traditional problem based learning in face-to-face groups (TPBL). The learning process consisted of four elements: an initial tutorial, a period of self-directed learning, a second tutorial and a laboratory session. During the initial tutorial students generated learning issues that they submitted to the research assistant. In the self-directed learning phase, students researched their learning issues and returned for the second tutorial with their findings. Students in the CMPBL groups interacted with the resource person electronically via email, chat room or bulletin board. At the second tutorial, groups shared information related to their learning issues and completed their products for the problem. RESULTS: There was no difference in learning outcomes between groups. The CMPBL group spent significantly more time on learning than the TPBL group. There was no overall difference between groups on generation of learning issues; however, there was a significant relationship between number of learning issues generated and higher score on the examination regardless of tutorial medium.

Computer-Assisted Instruction↗
PubMed2006

An exploration of the relationship between academic and experiential learning approaches in vocational education.

BACKGROUND: Research on individual learning approaches (or learning styles) is split in two traditions, one of which is biased towards academic learning, and the other towards learning from direct experience. AIMS: In the reported study, the two traditions are linked by investigating the relationships between school-based (academic) and work-based (experiential) learning approaches of students in vocational education programs. SAMPLES: Participants were 899 students of a Dutch school for secondary vocational education; 758 provided data on school-based learning, and 407 provided data on work-based learning, resulting in an overlap of 266 students from whom data were obtained on learning in both settings. METHODS: Learning approaches in school and work settings were measured with questionnaires. Using factor analysis and cluster analysis, items and students were grouped, both with respect to school- and work-based learning. RESULTS: The study identified two academic learning dimensions (constructive learning and reproductive learning), and three experiential learning dimensions (analysis, initiative, and immersion). Construction and analysis were correlated positively, and reproduction and initiative negatively. Cluster analysis resulted in the identification of three school-based learning orientations and three work-based learning orientations. The relation between the two types of learning orientations, expressed in Cramér's V, appeared to be weak. CONCLUSIONS: It is concluded that learning approaches are relatively context specific, which implies that neither theoretical tradition can claim general applicability.

Educational Status↗
PubMed2004

Implicit strategy affects learning in children with heavy prenatal alcohol exposure.

BACKGROUND: Learning and memory deficits are commonly reported in children with heavy prenatal alcohol exposure. Our recent work suggested that children with heavy prenatal alcohol exposure retained information as well as controls on a verbal learning test but not on a test of nonverbal learning and memory. To better understand the cause of this differential pattern of performance, the current study re-analyzed data from our previous study to determine if the presence of an implicit learning strategy may account, at least in part, for the finding of spared retention. METHODS: The current study examined verbal learning and memory abilities in 35 children with Fetal Alcohol Spectrum Disorders (FASD) and 34 nonexposed controls (CON) matched for age (9-16 years), sex, ethnicity, handedness, and socioeconomic status. Groups were compared on two measures of verbal learning, one with an implicit strategy (California Verbal Learning Test-Children's Version; CVLT-C) and one without (Verbal Learning subtest of the Wide Range Assessment of Memory and Learning; VL-WRAML). RESULTS: Children with FASD learned less information overall than children in the CON group. Both groups learned a greater percentage of information and reached a learning plateau earlier on the CVLT-C compared with the VL-WRAML. Groups also showed comparable rates of retention after a delay on the CVLT-C. In contrast, on the VL-WRAML, children with FASD showed poorer retention rates than children in the CON group. Interestingly, children with FASD did not differ from children in the CON group on CVLT-C semantic clustering scores for learning trials 1 through 3, and greater utilization of semantic clustering was correlated with better learning and memory performance in both groups. This overall pattern of results was not related to overall intellectual level. CONCLUSIONS: The finding of spared retention of verbal information on the CVLT-C in our earlier studies may be related to test characteristics of the CVLT-C rather than a finding of spared verbal retention per se, given that spared retention was not found on a separate test of verbal learning and memory without an implicit learning strategy. These results suggest that the use of an implicit strategy positively affected the ability of alcohol-exposed children to learn and retain new verbal information.

Adolescent↗
PubMed2003

Towards valid measures of self-directed clinical learning.

AIM: To compare the validity of different measures of self-directed clinical learning. METHODS: We used a quasi-experimental study design. The measures were: (1) a 23-item quantitative instrument measuring satisfaction with the learning process and environment; (2) free text responses to 2 open questions about the quality of students' learning experiences; (3) a quantitative, self-report measure of real patient learning, and (4) objective structured clinical examination (OSCE) and progress test results. Thirty-three students attached to a single firm during 1 curriculum year in Phase 2 of a problem-based medical curriculum formed an experimental group. Thirty-one students attached to the same firm in the previous year served as historical controls and 33 students attached to other firms within the same module served as contemporary controls. After the historical control period, experimental group students were exposed to a complex curriculum intervention that set out to maximise appropriate real patient learning through increased use of the outpatient setting, briefing and supported, reflective debriefing. RESULTS: The quantitative satisfaction instrument was insensitive to the intervention. In contrast, the qualitative measure recorded a significantly increased number of positive statements about the appropriateness of real patient learning. Moreover, the quantitative self-report measure of real patient learning found high levels of appropriate learning activity. Regarding outpatient learning, the qualitative and quantitative real patient learning instruments were again concordant and changed in the expected direction, whereas the satisfaction measure did not. An incidental finding was that, despite all attempts to achieve horizontal integration through simultaneously providing community attachments and opening up the hospital for self-directed clinical learning, real patient learning was strongly bounded by the specialty interest of the hospital firm to which students were attached. Assessment results did not correlate with real patient learning. CONCLUSIONS: Both free text responses and students' quantitative self-reports of real patient learning were more valid than a satisfaction instrument. One explanation is that students had no benchmark against which to rate their satisfaction and curriculum change altered their tacit benchmarks. Perhaps the stronger emphasis on self-directed learning demanded more of students and dissatisfied those who were less self-directed. Results of objective, standardised assessments were not sensitive to the level of self-directed, real patient learning. Despite an integrated curriculum design that set out to override disciplinary boundaries, students' learning remained strongly influenced by the specialty of their hospital firm.

Clinical Competence↗
PubMed2006

Validation of learning style measures: implications for medical education practice.

BACKGROUND: It is unclear which learners would most benefit from the more individualised, student-structured, interactive approaches characteristic of problem-based and computer-assisted learning. The validity of learning style measures is uncertain, and there is no unifying learning style construct identified to predict such learners. OBJECTIVE: This study was conducted to validate learning style constructs and to identify the learners most likely to benefit from problem-based and computer-assisted curricula. METHODS: Using a cross-sectional design, 3 established learning style inventories were administered to 97 post-Year 2 medical students. Cognitive personality was measured by the Group Embedded Figures Test, information processing by the Learning Styles Inventory, and instructional preference by the Learning Preference Inventory. The 11 subscales from the 3 inventories were factor-analysed to identify common learning constructs and to verify construct validity. Concurrent validity was determined by intercorrelations of the 11 subscales. RESULTS: A total of 94 pre-clinical medical students completed all 3 inventories. Five meaningful learning style constructs were derived from the 11 subscales: student- versus teacher-structured learning; concrete versus abstract learning; passive versus active learning; individual versus group learning, and field-dependence versus field-independence. The concurrent validity of 10 of 11 subscales was supported by correlation analysis. Medical students most likely to thrive in a problem-based or computer-assisted learning environment would be expected to score highly on abstract, active and individual learning constructs and would be more field-independent. CONCLUSIONS: Learning style measures were validated in a medical student population and learning constructs were established for identifying learners who would most likely benefit from a problem-based or computer-assisted curriculum.

Cognition↗
PubMedDate not supplied

[Influence of attention on an auditory-verbal learning test in schizophrenic patients].

Schizophrenic patients are known to feature alterations in their cognitive performances, principally in executive functions, attention and memory. In this last domain, studies have shown a relatively severe and global deficit, which can be assessed in chronic and first episode patients. It seems that the memory dysfunction is independent of age and intellectual level, but does correlate with negative psychopathology and global functioning. In the study of memory dysfunction, attentional capacities, information processing and symptomatology have to be considered as determining factors. It has been shown that patients with schizophrenia perform poorly in selective attention tasks and that this deficit may interfere with learning. In the same way, the slowing of information processing contributes to a superficial and incomplete learning. The impact of symptomatology has also to be considered, as negative and depressive symptoms are linked to mnesic performances. The majority of studies bearing on working memory and schizophrenia show an alteration of performances, but studies on long term memory are more equivocal. Procedural memory seems to be preserved, while declarative memory is impaired. These results support the hypothesis that in schizophrenia, memory processes that are consciously controlled are impaired, contrary to implicit learning which may be intact. Nevertheless, studies bearing on semantic memory and episodic memory show controversial results. Still, many authors argue that schizophrenic patients have difficulties in recalling learned material, specially when a delay or a interfering task are introduced in the test. Besides, the schizophrenic subjects do not use the semantic properties of the words, as well as the control subjects, when they have to learn a words list for example. The main goal of the present study was to examine the auditory-verbal learning capacities of 31 schizophrenic patients (20 men and 11 women, 19-56 years old), compared to 27 healthy subjects (11 men and 16 women, 23-56 years old). All subjects received an evaluation including the Rey Auditory-Verbal Learning Test, used to study the progressive acquisition of 15 disyllabic words which are successively orally presented five times to the subject. About forty-five minutes after the last of the five immediate recalls, the delayed recall is assessed and a percentage of retention is also calculated. Visual reasoning and attention capacities were studied with the Progressive Matrix and the d2 encumbrance test respectively. Global psychiatric symptomatology of the patients group was assessed with the Brief Psychiatric Rating Scale. Considering the literature existing on the verbal learning capacities of schizophrenic patients, it was expected that the patients would perform poorly and learn slower than controls. The initial learning of the material, which is a critical stage for schizophrenic patients, was studied with particular attention as well as the effect of the introduction of a delay upon the recall of the words list. A secondary objective of the study was to investigate the role of visual reasoning and attention upon auditory-verbal learning process. According to published studies, it is expected that schizophrenic patients manifest some impairment in the domains of visual reasoning and attention. The question is to know whether it alters performances in the auditory-verbal learning test or not. Finally, the links between clinical characteristics of the patients, like age and illness duration, and their learning performances were explored. Statistical analysis included first a descriptive analysis of data to examine differences between the two groups. Second, ANCOVAs were used in order to control the respective impact of educational level, attention capacities and verbal reasoning capacities upon learning performances. Third, Spearman's correlations were used to detect links between clinical characteristics of the patients and learning performances. The comparisons between patients and controls confirmed that schizophrenic patients scored less in the attentional and visual reasoning tasks. They also featured a lower educational level compared to the healthy subjects. In the auditory-verbal learning test, the patients showed altered performances in the five recalls, as well as in the delayed recall and for the retention percentage. In order to control the impact of educational level, attentional and visual reasoning capacities, these parameters were introduced in the statistical analyses. Educational level did not influence memory alterations in the schizophrenic group. However, attention and, to a lesser extend, visual reasoning had an impact on the comparison of memory scores: when controlling attention, almost no significant group effect remained. Finally, the exploratory analyses of links between clinical characteristics and memory only revealed the presence of a significant negative correlation between illness duration and learning performances. Thus, the analyze of data showed that schizophrenic subjects featured poor performances in the domains of attention, verbal reasoning and auditory-verbal memory. Further analyses taking into account group differences on attention suggest that the impairment featured by schizophrenic patients in the domain of verbal memory strongly relies on an attentional deficit. These results are discussed according to the existing literature and methodological limitations. Clinical implications are also discussed.

Adult↗
PubMedDate not supplied

Molecular, cellular, and neuroanatomical substrates of place learning.

Learning and remembering the location of food resources, predators, escape routes, and immediate kin is perhaps the most essential form of higher cognitive processing in mammals. Two of the most frequently studied forms of place learning are spatial learning and contextual conditioning. Spatial learning refers to an animal's capacity to learn the location of a reward, such as the escape platform in a water maze, while contextual conditioning taps into an animal's ability to associate specific places with aversive stimuli, such as an electric shock. Recently, transgenic and gene targeting techniques have been introduced to the study of place learning. In contrast with the abundant literature on the neuroanatomical substrates of place learning in rats, very little has been done in mice. Thus, in the first part of this article, we will review our studies on the involvement of the hippocampus in both spatial learning and contextual conditioning. Having demonstrated the importance of the hippocampus to place learning, we will then focus attention on the molecular and cellular substrates of place learning. We will show that just as in rats, mouse hippocampal pyramidal cells can show place specific firing. Then, we will review our evidence that hippocampal-dependent place learning involves a number of interacting physiological mechanisms with distinct functions. We will show that in addition to long-term potentiation, the hippocampus uses a number of other mechanisms, such as short-term-plasticity and changes in spiking, to process, store, and recall information. Much of the focus of this article is on genetic studies of learning and memory (L&M). However, there is no single experiment that can unambiguously connect any cellular or molecular mechanism with L&M. Instead, several different types of studies are required to determine whether any one mechanism is involved in L&M, including (i) the development of biologically based learning models that explain the involvement of a given mechanism in L&M, (ii) lesion experiments (genetics and pharmacology), (iii) direct observations during learning, and (iv) experiments where learning is triggered by turning on the candidate mechanism. We will show how genetic techniques will be key to unraveling the molecular and cellular basis of place learning.

Animals↗
PubMed2004

Analysis and design of behavioral experiments to characterize population learning.

In population learning studies, between-subject response differences are an important source of variance that must be characterized to identify accurately the features of the learning process common to the population. Although learning is a dynamic process, current population analyses do not use dynamic estimation methods, do not compute both population and individual learning curves, and use learning criteria that are less than optimal. We develop a state-space random effects (SSRE) model to estimate population and individual learning curves, ideal observer curves, and learning trials, and to make dynamic assessments of learning between two populations and within the same population that avoid multiple hypothesis tests. In an 80-trial study of an NMDA antagonist's effect on the ability of rats to execute a set-shift task, our dynamic assessments of learning demonstrated that both the treatment and control groups learned, yet, by trial 35, the treatment group learning was significantly impaired relative to control. We used our SSRE model in a theoretical study to evaluate the design efficiency of learning experiments in terms of the number of animals per group and number of trials per animal required to characterize learning differences between two populations. Our results demonstrated that a maximum difference in the probability of a correct response between the treatment and control group learning curves of 0.07 (0.20) would require 15 to 20 (5 to 7) animals per group in an 80 (60)-trial experiment. The SSRE model offers a practical approach to dynamic analysis of population learning and a theoretical framework for optimal design of learning experiments.

Algorithms↗
PubMed2000

An appraisal of medical students' reflection-in-learning.

INTRODUCTION: How do students reflect as they strive for some control of learning early in their clinical activities? The purpose of this study was to examine the reflection-in-learning profile of medical students as they started their clinical apprenticeship. METHODS: A measure of reflection-in-learning was used to appraise the level and direction of change of reflection in relation to a course experience. The study involved 103 medical students of both sexes who were beginning clinical activities. Assessments of self-regulation of learning, of the meaningfulness of the learning experience, and of diagnostic thinking were also obtained. RESULTS: The results showed that 81% of the students had an increase in scores for reflection-in-learning between the beginning and the end of a course. At the end of the course, the level of reflection-in-learning was significantly associated with self-perceived competence for self-regulated learning and with the meaningfulness of the learning experience. In the following term, students who had high reflection-in-learning scores at the end of the course had higher grade-point averages and greater self-reported diagnostic ability in comparison with those with low scores. CONCLUSIONS: There was some evidence of an improved quality of reflection as the students strive for some control of learning. Overall, the findings support the idea that a greater effort at reflection is associated with a more positive learning experience. They also suggest that reflection-in-learning is related to readiness for self-regulation of learning and may be conducive to enhanced diagnostic ability. In conclusion, measuring reflection-in-learning may be a useful tool in the appraisal of medical students' learning profiles.

Attitude↗
PubMed2002

Psychological myths in e-learning.

Traditional education and training has paid scant attention to the psychology of learning. Despite detailed research into motivation, distribution and reinforcement, most current methods of delivery still rely on a supply-led, lecture and classroom-based model that flies in the face of the theory. With e-learning we have a chance to reflect on this gap between theory and practice. E-learning, in the sense of web-based learning, is a new discipline but the psychology of learning has a much longer pedigree. This paper relates some common myths about e-learning back to some major themes in the psychology of learning. Is e-learning faster and more effective? Many people get the wrong learning at the wrong time. Can e-learning help with prerequisite knowledge? Should the learning be massed or distributed, i.e. all at once or little and often? There are also the issues of motivation and cognitive engagement. How can e-learning motivate learners or how can we motivate learners into using this new medium? What type of cognitive engagement is necessary for learning? Traditional 'sheep-dip' methods of learning are poor on reinforcement. Can e-learning help reinforce learning?

Education, Distance↗
PubMed2005

Ambulatory teaching: do approaches to learning predict the site and preceptor characteristics valued by clerks and residents in the ambulatory setting?

BACKGROUND: In a study to determine the site and preceptor characteristics most valued by clerks and residents in the ambulatory setting we wished to confirm whether these would support effective learning. The deep approach to learning is thought to be more effective for learning than surface approaches. In this study we determined how the approaches to learning of clerks and residents predicted the valued site and preceptor characteristics in the ambulatory setting. METHODS: Postal survey of all medical residents and clerks in training in Ontario determining the site and preceptor characteristics most valued in the ambulatory setting. Participants also completed the Workplace Learning questionnaire that includes 3 approaches to learning scales and 3 workplace climate scales. Multiple regression analysis was used to predict the preferred site and preceptor characteristics as the dependent variables by the average scores of the approaches to learning and perception of workplace climate scales as the independent variables. RESULTS: There were 1642 respondents, yielding a 47.3% response rate. Factor analysis revealed 7 preceptor characteristics and 6 site characteristics valued in the ambulatory setting. The Deep approach to learning scale predicted all of the learners' preferred preceptor characteristics (beta = 0.076 to beta = 0.234, p < .001). Valuing preceptor Direction was more strongly associated with the Surface Rational approach (beta = .252, p < .001) and with the Surface Disorganized approach to learning (beta = .154, p < 001) than with the Deep approach. The Deep approach to learning scale predicted valued site characteristics of Office Management, Patient Logistics, Objectives and Preceptor Interaction (p < .001). The Surface Rational approach to learning predicted valuing Learning Resources and Clinic Set-up (beta = .09, p = .001; beta = .197, p < .001). The Surface Disorganized approach to learning weakly negatively predicted Patient Logistics (beta = -.082, p = .003) and positively the Learning Resources (beta = .088, p = .003). Climate factors were not strongly predictive for any studied characteristics. Role Modeling and Patient Logistics were predicted by Supportive Receptive climate (beta = .135, p < .001, beta = .118, p < .001). CONCLUSION: Most site and preceptor characteristics valued by clerks and residents were predicted by their Deep approach to learning scores. Some characteristics reflecting the need for good organization and clear direction are predicted by learners' scores on less effective approaches to learning.

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