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At least 19 recordsLinked to original sources
PubMed2002

The quantitative evaluation of functional neuroimaging experiments: mutual information learning curves.

Learning curves are presented as an unbiased means for evaluating the performance of models for neuroimaging data analysis. The learning curve measures the predictive performance in terms of the generalization or prediction error as a function of the number of independent examples (e.g., subjects) used to determine the parameters in the model. Cross-validation resampling is used to obtain unbiased estimates of a generic multivariate Gaussian classifier, for training set sizes from 2 to 16 subjects. We apply the framework to four different activation experiments, in this case [(15)O]water data sets, although the framework is equally valid for multisubject fMRI studies. We demonstrate how the prediction error can be expressed as the mutual information between the scan and the scan label, measured in units of bits. The mutual information learning curve can be used to evaluate the impact of different methodological choices, e.g., classification label schemes, preprocessing choices. Another application for the learning curve is to examine the model performance using bias/variance considerations enabling the researcher to determine if the model performance is limited by statistical bias or variance. We furthermore present the sensitivity map as a general method for extracting activation maps from statistical models within the probabilistic framework and illustrate relationships between mutual information and pattern reproducibility as derived in the NPAIRS framework described in a companion paper.

Adult↗
PubMed2005

The learning curve in learning the curve: a review of Nuss procedure in teenagers.

BACKGROUND: The Nuss procedure is a new minimally invasive repair for pectus excavatum that was first published in 1998. Modifications in technique are constantly evolving to minimize complications, especially bar displacement, which are higher in adolescents and adults. The present study reviews our early experience with this procedure in a much older group of children than previously reported and suggests an alternative method of avoiding bar displacement. METHODS: Retrospective chart review was carried out on 78 consecutive patients who underwent the Nuss procedure between December 1999 and January 2004. All patients underwent a uniform technique using bilateral lateral stabilisers and thoracoscopy was not used. Operative details, subjective cosmetic results and complication rates were assessed. RESULTS: The mean age was 15.4 +/- 3.2 years. Single bars were used in 95%, double bars in 5%. The defect was asymmetrical in 26%. The defect was mild in 7%, moderate in 59% and severe in 34%. The median length of stay was 6.0 days (range 4-11). Total operating time was 58 min (range 35-95). Patient controlled analgesia (morphine) for pain relief was used for 105 h (range 61-169) or 4.4 days; the epidural infusion was stopped 1 day earlier. Cosmetic results were excellent in 80.3%. There was residual asymmetry in 75% of the asymmetrical defects although all were improved. Complications included eight (10%) reoperations for bar displacement. This was related to the learning curve as seven of these occurred in the first 2 years of the series. Removal of the bar has been accomplished in 31 (40%) patients. This was elective in all but four patients (three early removals for pain and one for infection). CONCLUSIONS: The Nuss procedure gives good results even in teenagers. Modification of technique and increased experience has reduced complications. The use of bilateral lateral stabilisers without additional wire fixation is an alternative method to avoid bar displacement.

Adolescent↗
PubMed1997

Estimating Learning Curves of Concept Learning.

In this paper, we describe an approximation method which enables us to study the average generalization performance of learning directly via hypothesis testing inequalities. This unites the learning and the hypothesis testing in a common viewpoint. In particular, we investigate learning curves of a so-called ill-disposed learning algorithm, which can provide useful implications regarding the problem of overfitting from a practical and yet scientific viewpoint. The learning problem is stated in the probably approximately correct (PAC) learning model, but only the average generalization performance is addressed. The resulting bounds are directly related to the number of system weights. The advantages of the theory are that it alleviates the practical pessimism frequently claimed for the results of the VC theory, and provides general insights. We illustrate the results with some numerical simulations. Copyright 1997 Elsevier Science Ltd.

Journal Article↗
PubMedDate not supplied

Statistics in physiology and pharmacology: a slow and erratic learning curve.

1. Learning how to apply statistical analyses to the results of experimental or clinical studies may take a lifetime of trial (and sometimes error), as it has done in the author's case. There is no evidence that biomedical investigators of the present generation are on a steeper learning curve. Gross misunderstandings of the purpose and functions of statistical analysis are apparent in applications to research grant-giving bodies and ethics committees, in manuscripts submitted to journals and sometimes in published papers. 2. Although estimation of minimal group (sample) size for a given power is an essential step in planning clinical studies, it seems to be used rarely in laboratory experimental work. This is despite exhortations to restrict the number of animals used to a minimum. 3. Most investigators use hypothesis testing to analyse their results, but their understanding of the meaning of the resultant P-values is slight. 4. A flaw found almost universally in biomedical manuscripts is to make multiple inferences from the results of a single study. The goal of statistical analysis is to maintain the familywise type I error rate (risk of false-positive inference) at a predetermined level (usually 5%). But, when multiple inferences are made from the same experiment, the risk of false-positive error is inflated. There are two solutions to this problem: (i) use a multiple comparison procedure to control the familywise type I error rate; and (ii) test a single, global hypothesis. 5. Biomedical investigators have been quick to acquire computer statistics software and to use it to analyse their experiments. However, they have been slow to recognize the limitations of this software. These include: (i) inadequate documentation of routines, so that neither the user nor the reader of published papers can be sure how the tests have been executed; (ii) flawed algorithms for the execution of statistical procedures; and (iii) failure to recognize that the best software for their purposes is that which takes them just beyond their statistical horizons. 6. The obvious solution to these difficulties is to recruit a biomedical statistician into every research group, at a relatively trivial cost. However, properly qualified biostatisticians are in desperately short supply in Australia. It follows that research groups, national grant-giving agencies and academic institutions must make provision for the proper training and subsequent employment of biostatisticians.

Data Interpretation, Statistical↗
PubMed1993

Metabolic and nutritional support of the intensive care patient. Ascending the learning curve.

The learning curve of nutritional support in the critically ill began with the amelioration of the effects of starvation in patients with a disabled intestine. Next, there was an appreciation that feeding formulas could be tailored to support patients with specific organ insufficiencies. Then it was realized that feeding enterally has distinct advantages over feeding parenterally. In addition to a decrease in catheter-related sepsis, there was noted a distinct decrease in "remote site" sepsis. In fact, good scientific reasons have been identified to explain why this occurs, such as maintaining the competency of the intestine against a translocation of endotoxin and bacteria and "turn-on" of the stress response. Further, we now know that specific nutrients can produce desirable pharmacologic effects. In the future, feeding formulae will be devised that continue to modify the patient's response to illness favorably. Another important consideration is to begin nutritional support as soon as possible--i.e., on the day of admission, if appropriate. The critical care specialist should be expert in these techniques, with the goal of eliminating malnutrition as a confounding variable in the clinical course of the intensive care unit patient.

Critical Care↗
PubMed2002

Comparing objective and subjective learning curves: judgments of learning exhibit increased underconfidence with practice.

When participants studied a list of paired associates for several study-test cycles, their judgments of learning (JOLs) exhibited relatively good calibration on the 1st cycle, with a slight overconfidence. However, a shift toward marked underconfidence occurred from the 2nd cycle on. This underconfidence-with-practice (UWP) effect was very robust across several experimental manipulations, such as feedback or no feedback regarding the correctness of the answer, self-paced versus fixed-rate presentation, different incentives for correct performance, magnitude and direction of associative relationships, and conditions producing different degrees of knowing. It was also observed both in item-by-item JOLs and in aggregate JOLs. The UWP effect also occurred for list learning and for the memory of action events. Several theoretical explanations for this counterintuitive effect are discussed.

Adult↗
PubMed2000

Exponential or polynomial learning Curves? - case-based studies

Learning curves exhibit a diversity of behaviors such as phase transition. However, the understanding of learning curves is still extremely limited, and existing theories can give the impression that without empirical studies (e.g., cross validation), one can probably do nothing more than qualitative interpretations. In this note, we propose a theory of learning curves based on the idea of reducing learning problems to hypothesis-testing ones. This theory provides a simple approach that is potentially useful for predicting and interpreting (a diversity of) learning curve behaviors qualitatively and quantitatively, and it applies to finite training sample size and finite learning machine and for learning situations not necessarily within the Bayesian framework. We illustrate the results by examining some exponential learning curve behaviors observed in Cohn and Tesauro (1992)'s experiment.

Journal Article↗
PubMed1995

What is the learning curve for laparoscopic colectomy?

Learning curves have been described for a variety of laparoscopic procedures including cholecystectomy, tubal ligation, and diagnostic laparoscopy. Although multiple series of laparoscopic colectomies have appeared, there is little information regarding the learning curve associated with this advanced procedure. The purpose of this study is to present a single team's experience with laparoscopic colon resection to allow the description of our learning curve. The data collected included age, sex, operating room time, recovery of bowel function, days to clear liquid, hospital stay, conversion, complications, indication for operation, and site of resection. Sixty consecutive patients were analyzed and divided into three groups: First 20, Second 20, and Third 20. There were no significant differences between the three groups with respect to age, male versus female ratio, indications for surgery, or site of resection. However, the complexity of surgical procedures and the incidence of previous major abdominal surgery increased steadily with experience. The incidence of pulmonary complications was 30 per cent in the First 20 group and decreased to 5 per cent for the next two groups. The conversion rate was 20 per cent for the First 20 group, 45 per cent for the Second 20 group, and decreased to 10 per cent for the Third 20 group.(ABSTRACT TRUNCATED AT 250 WORDS)

Abdomen↗
PubMed1995

The laparoscopic learning curve.

To characterize the learning curve for laparoscopic cholecystectomy, we compared the first 47 cases (group A), which were performed by two senior attending surgeons who assisted each other when the procedure was introduced into clinical practice (1990-1991), with the first 46 cases (group R) performed by two surgical chief residents who were assisted by members of the teaching faculty in 1992-1993. The patient groups were comparable in terms of age, sex, and anesthetic class, but pathologically proven acute cholecystitis was more common in group R (33% vs. 9%; p < 0.005). To analyze operative procedures and outcomes, we compared operative time, frequency of successful operative cholangiography (attempted in all cases), frequency of conversion to open cholecystectomy, major complication rate, and days of postoperative stay for all patients and for those without complications. Of these parameters, only operative time for nonacute cases differed significantly between the groups (144 min for group A vs. 114 min for group R; p < 0.05). Complications in group A included one ductal injury and one case of postoperative pancreatitis; group R had one ductal injury and two cases of postoperative bleeding. We conclude that (a) the learning curve has similar structure for senior surgeons and resident trainees; and (b) the resident learning curve is not hazardous when teaching assistants are trained in the procedure, which has implications for safe instruction and proctoring of residents and staff.

Acute Disease↗
PubMed2005

[Learning curve--calculation and value in laparoscopic surgery].

The learning curve shows the progress in mastering a new method. It is completed when the monitored parameters reach a steady state and when the final results can be compared with literature. The earlier used analysis of the performance-improvement with its "on the spots" appraisals at certain time-intervals is replaced by a continuous assessment. The multimode learning curve is particularly useful for it, because not only one parameter (f.e. operation-time), but also several important factors can be put together into one single graphic. For the operation-time, the Moving Average Method is useful. For incidents, which may happen or not like a conversion from laparoscopy to laparotomy as well as complications, the Cusum-method is of practical use. The learning curves of the technique of laparoscopic cholecystectomy, colo-rectal surgery, fundoplicatio and hernia surgery have been completed. Also, the learning curve of the industry is well advanced. Reliable data for the learning curves of individual surgeons for certain operations cannot be given, as, only now, young doctors are being trained on a large scale in laparoscopic technique as used to be the case in the open abdominal surgery. This will influence greatly the learning curves and will shorten the time till their completion. Different bias concerning the individual surgeons and their clinics prohibit the production of comparable curves. Several factors like the patient respectively his abdomen are complicating all this. That's why the learning curves cannot be used as benchmarks to compare different surgeons or clinics, as long as no valid scoring system concerning the complexity of a surgical intervention exists. Learning curves which become quality curves after reaching a steady state, can be used for the individual monitoring of a surgeon's performance and serve as a quality measurement of a clinic. The learning curves of the laparoscopic cholecystectomy, fundoplicatio, colo-rectal surgery and hernia surgery are discussed in particular The mandatory number of operations needed to learn a new method cannot yet be established today, even if all the existing data are consulted. Therefore, the learning curve is a useful instrument to monitor the individual progress and the results of a clinic in the meaning of an individual quality-management. After completion of the learning curve, a quality curve using the same parameters will be given, which shows the deviations of its own standard.

Cholecystectomy, Laparoscopic↗
PubMed2005

The learning curve for investigational surgery: lessons learned from laparoscopic diaphragm pacing for chronic ventilator dependence.

BACKGROUND: Electrical stimulation of the phrenic nerve motor point of the diaphragm through laparoscopic implantation of a pacing system is an option for high spinal cord-injured patients with chronic respiratory insufficiency. This study assesses the operative learning curve for the initial series of patients. METHOD: A series of six patients underwent laparoscopic placement of a diaphragm pacing system. The operative procedure was divided into the following four steps for analysis and rapid adjustment after each operation: exposure of the diaphragm, mapping of the phrenic nerve motor point, implantation of the pacing electrodes, and final routing of the wires to the external system. RESULTS: The first case required two operations, and the second case was unsuccessful because of a nonfunctioning phrenic nerve that led to a change in the preoperative screening criteria. The operative time decreased from 469 min for the first operation to 165 min for the sixth operation. The significant time decrease can be attributed to changes in the mapping and routing aspects of the operation. Key changes during this series that helped to reduce the operative time include abandonment of a software-dependent mapping technique, development of a grid algorithm for mapping, software improvement to increase the speed of stimulation and mapping, refinement of the mapping probe to maintain adequate suction on the diaphragm, shortening of the electrode lengths, and experience with the implantation of connections to the external electrodes. Presently, all five of the successfully implanted patients can be maintained on prolonged ventilatory support with the device. CONCLUSION: Analysis of every step of this investigational procedure enabled us to make rapid changes in surgical protocol, leading to decreases in operative times and expectant improvements in patient safety and efficacy. In this series, analysis was the key to developing a low-risk cost-effective outpatient diaphragm pacing system.

Adult↗
PubMed2001

Statistical assessment of the learning curves of health technologies.

OBJECTIVES: (1) To describe systematically studies that directly assessed the learning curve effect of health technologies. (2) Systematically to identify 'novel' statistical techniques applied to learning curve data in other fields, such as psychology and manufacturing. (3) To test these statistical techniques in data sets from studies of varying designs to assess health technologies in which learning curve effects are known to exist. METHODS - STUDY SELECTION (HEALTH TECHNOLOGY ASSESSMENT LITERATURE REVIEW): For a study to be included, it had to include a formal analysis of the learning curve of a health technology using a graphical, tabular or statistical technique. METHODS - STUDY SELECTION (NON-HEALTH TECHNOLOGY ASSESSMENT LITERATURE SEARCH): For a study to be included, it had to include a formal assessment of a learning curve using a statistical technique that had not been identified in the previous search. METHODS - DATA SOURCES: Six clinical and 16 non-clinical biomedical databases were searched. A limited amount of handsearching and scanning of reference lists was also undertaken. METHODS - DATA EXTRACTION (HEALTH TECHNOLOGY ASSESSMENT LITERATURE REVIEW): A number of study characteristics were abstracted from the papers such as study design, study size, number of operators and the statistical method used. METHODS - DATA EXTRACTION (NON-HEALTH TECHNOLOGY ASSESSMENT LITERATURE SEARCH): The new statistical techniques identified were categorised into four subgroups of increasing complexity: exploratory data analysis; simple series data analysis; complex data structure analysis, generic techniques. METHODS - TESTING OF STATISTICAL METHODS: Some of the statistical methods identified in the systematic searches for single (simple) operator series data and for multiple (complex) operator series data were illustrated and explored using three data sets. The first was a case series of 190 consecutive laparoscopic fundoplication procedures performed by a single surgeon; the second was a case series of consecutive laparoscopic cholecystectomy procedures performed by ten surgeons; the third was randomised trial data derived from the laparoscopic procedure arm of a multicentre trial of groin hernia repair, supplemented by data from non-randomised operations performed during the trial. RESULTS - HEALTH TECHNOLOGY ASSESSMENT LITERATURE REVIEW: Of 4571 abstracts identified, 272 (6%) were later included in the study after review of the full paper. Some 51% of studies assessed a surgical minimal access technique and 95% were case series. The statistical method used most often (60%) was splitting the data into consecutive parts (such as halves or thirds), with only 14% attempting a more formal statistical analysis. The reporting of the studies was poor, with 31% giving no details of data collection methods. RESULTS - NON-HEALTH TECHNOLOGY ASSESSMENT LITERATURE SEARCH: Of 9431 abstracts assessed, 115 (1%) were deemed appropriate for further investigation and, of these, 18 were included in the study. All of the methods for complex data sets were identified in the non-clinical literature. These were discriminant analysis, two-stage estimation of learning rates, generalised estimating equations, multilevel models, latent curve models, time series models and stochastic parameter models. In addition, eight new shapes of learning curves were identified. RESULTS - TESTING OF STATISTICAL METHODS: No one particular shape of learning curve performed significantly better than another. The performance of 'operation time' as a proxy for learning differed between the three procedures. Multilevel modelling using the laparoscopic cholecystectomy data demonstrated and measured surgeon-specific and confounding effects. The inclusion of non-randomised cases, despite the possible limitations of the method, enhanced the interpretation of learning effects. CONCLUSIONS - HEALTH TECHNOLOGY ASSESSMENT LITERATURE REVIEW: The statistical methods used for assessing learning effects in health technology assessment have been crude and the reporting of studies poor. CONCLUSIONS - NON-HEALTH TECHNOLOGY ASSESSMENT LITERATURE SEARCH: A number of statistical methods for assessing learning effects were identified that had not hitherto been used in health technology assessment. There was a hierarchy of methods for the identification and measurement of learning, and the more sophisticated methods for both have had little if any use in health technology assessment. This demonstrated the value of considering fields outside clinical research when addressing methodological issues in health technology assessment. CONCLUSIONS - TESTING OF STATISTICAL METHODS: It has been demonstrated that the portfolio of techniques identified can enhance investigations of learning curve effects. (ABSTRACT TRUNCATED)

Cholecystectomy↗
PubMed2004

The learning curve for a colonoscopy simulator in the absence of any feedback: no feedback, no learning.

BACKGROUND: The hypothesis of this study is that working on the simulator without a structured feedback does not change performance; hence, any effects shown after structured feedback would amount to useful learning of the procedure. The aim was to investigate the learning curve for the HT Immersion Medical Colonoscopy Simulator without any structured feedback. This could then be potentially applied to validate the learning curve on the simulator when structured feedback is provided. There are no previous studies on this matter. METHODS: Candidates were asked to perform colonoscopy on the HT Immersion Medical Colonoscopy Simulator. Modules 3 and 4 were used at random. In total, each candidate was asked to perform five consecutive virtual colonoscopies on the same module. These five episodes were collectively referred to as one trial. A time result of 3,600 sec (1 h) was used to denote perforation. No guidance or feedback was given to candidates before, during, or after each procedure. A total of 26 postgraduate doctors were recruited, including nine research fellows, five preregistration house officers, six specialist registrars, and six consultants. Fourteen candidates recorded five attempts each (i.e., one trial each) on the same module of the colonoscopy simulator (14 trials over 70 episodes). Another 12 candidates recorded five attempts (i.e., one trial each) on two modules of the colonoscopy simulator (24 trials over 120 episodes). Hence, 190 episodes were recorded in total, representing 38 trials. RESULTS: There was no improvement in performance on the simulator from first attempt to the fifth in the absence of feedback. If there was any initial gain in any measurable outcome, this was lost in subsequent attempts indicating lack of learning. The outcomes measured included time taken to complete the test, percentage of the mucosa visualized, depth of the instrument inserted, and the path length used. The results were statistically significant for all outcomes. CONCLUSIONS: This study demonstrates that in the absence of feedback, it is not possible to improve performance on the HT Immersion Medical Colonoscopy Simulator. Thus, there is no learning curve for the machine. The information from this study is vital for using the simulators in training and assessment because any improvement in learning curves shown after training on simulators can be presumed to be due to learning the procedure and not the simulator.

Clinical Competence↗
PubMed2005

Assessment of the learning curve for lumbar microendoscopic discectomy.

OBJECTIVE: An understanding of the learning curve of a new surgical procedure is essential for its safe clinical integration, teaching, and assessment. This knowledge is currently deficient for lumbar microendoscopic discectomy (MED). The present article aims to profile the learning curve for MED of an individual surgeon in a hospital not previously exposed to this procedure. METHODS: The first 35 cases of MED for posterolateral lumbar disc prolapse causing radiculopathy performed at the Princess Alexandra Hospital, Brisbane, Australia, were studied prospectively. The learning curve was assessed using surgery time, conversion rate, complication rate, surgeon "comfort," and key learning steps. RESULTS: The duration of surgical operating time decreased over the course of the study, initially rapidly and then more gradually. There were three conversions to open discectomy in the first 7 cases and none in the next 28 cases. The complexity of cases increased over the series, and the complication rate decreased. The asymptote of the learning curve seems to be approximately 30 cases. The specific learning tasks of MED include lateral lamina radiology, scope vision, visuospatial orientation, smaller field of view, angle of approach and tube position, and care and handling of endoscope equipment. CONCLUSION: A learning curve for MED has been demonstrated. Further assessment of this curve for a population of surgeons is necessary before a clinical assessment of open discectomy versus MED can be embarked upon.

Adult↗
PubMed2002

Comparison of robotic versus laparoscopic skills: is there a difference in the learning curve?

OBJECTIVES: To evaluate the learning curve between robot-assisted and manual laparoscopic suturing, as well as to assess other skills. Laparoscopic reconstructive procedures have been limited by instrumentation, small working spaces, and fixed angles at the trocar level to place sutures. Robot-assisted laparoscopic suture placement may provide one means of increasing dexterity and facilitating laparoscopic reconstructive procedures. METHODS: Eight physicians participated in this study. A series of five trials were performed to assess dexterity (task 1) and free-hand suturing (task 2). Each task was performed using robot-assisted and manual laparoscopy. The participants were categorized as novice and experienced laparoscopists. Task 1 involved passing sutures through the eye of seven needles positioned 1 cm apart in a P configuration. Task 2 involved tying one surgeon's knot, followed by two subsequent knots. RESULTS: The average time for trials 1 and 5 of task 1, robot-assisted laparoscopy, was 242.6 and 101.8 seconds, respectively (P <0.001). Both groups demonstrated a statistically significant difference (P <0.001) between the first and last trial. The average time for trials 1 and 5 of task 1, manual laparoscopy, was 205.3 and 169 seconds, respectively. The differences in the learning curves for robot-assisted and manual laparoscopy were statistically significant in favor of robotic assistance. Manual laparoscopic suturing did not demonstrate as much of a difference for the experienced surgeon. Overall, the difference in improvement between robot-assisted and manual laparoscopy was not statistically significant. CONCLUSIONS: Robot-assisted laparoscopic allows suturing and dexterity skills to be performed quicker than does manual laparoscopy.

Clinical Competence↗
PubMed2002

Tension-free vaginal tape for stress urinary incontinence: Is there a learning curve?

AIM: To assess the learning curve characteristics of the first 30 tension-free vaginal tape (TVT) procedures carried out in our medical center and to evaluate its safety and short-term effectiveness. METHODS: A total of 30 incontinent women with urodynamically proven SUI were enrolled. None had undergone any previous anti-incontinence procedure. All were operated on by one surgeon, in accordance with the technique described by Ulmsten et al. in 1996. Mean follow-up was 11.4+/- 3.6 months (range, 5-17 months). RESULTS: Five (17%) bladder perforations occurred at the beginning of the study, due to inadvertent insertion of the applicator. All perforations were identified by intraoperative cystoscopy. Five other patients (17%) had increased intraoperative bleeding (>200 mL) necessitating vaginal tamponade. Blood transfusions were not required. Eight (27%) patients had immediate postoperative voiding difficulties, necessitating catheterization for 2-10 days, but none needed long-term catheterization. There was no local infection or rejection of the Prolene tape was found. All patients were subjectively cured of their stress incontinence; however, urodynamic evaluation revealed "asymptomatic genuine stress incontinence" in one patient. Sixteen of 21 patients (80%) with preoperative urge syndrome, had persistent postoperative symptoms. No patient developed de novo urge incontinence. CONCLUSION: The TVT operation is a new, minimally invasive surgical procedure with excellent short- and medium-term cure rates. However, there is a definite learning curve, and we believe that the operation should only be performed by experienced surgeons.

Aged↗
PubMed1986

Statistical mixture decomposition as a method for type analysis of learning curves.

A method for type analysis of learning curves, based on the statistical mixture decomposition, is described. Some critical points in current data-analytic techniques are discussed. The mathematical rationale of the new method is outlined in a brief sketch. The possibilities of the method are documented by two examples. In the first study, done on simulated lata of a known structure (N = 200, 2 classes), it was possible to distinguish, with an average performance of 82%, between two types, and to reproduce their original curves. In the second study data from experiments in classical eye-lid conditioning in man were analysed (N = 80). The decomposition procedure resulted into the classification into four groups, with pronounced inter-class differences in the course of respective learning curves. The variety of class curves ranges from a group with only few CRs (C1, N = 26), through a group with an initial increase and final decrease in CR frequency (C2, N = 16), a group with an apparently biphasic course of CR frequency (C3, N = 20), to a group with a rapid increase of CR and then stable course of CR frequency (C4, N = 18). The results are consistent with earlier findings concerning the existence of distinct types of learning curves. The problem of interpretation is briefly discussed. The method can be applied principally to any problems, where different types of time development trends of an alternative response are to be distinguished.

Conditioning, Classical↗