Duncan J. MacCrimmon

Attention/information processing, neuropsychological functioning, and thought disorder during the acute and partial recovery phases of schizophrenia: A longitudinal study

Schizophrenic subjects were administered the span of apprehension task, which is a measure of visual information processing; two neuropsychological tests; and measures of specific aspects of thought disorder and general clinical state. The measures were administered both when patients were acutely disturbed and when they were partially recovered. Normal control subjects were tested over a comparable 12-week interval. Improvements in both overall clinical condition and specific aspects of thought disorder occurred in the schizophrenic patients during this time. The patients, however, continued to show impaired information processing, indicating that the span of apprehension task is sensitive to schizophrenic dysfunction across wide variations in clinical state and, therefore, may be a marker of vulnerability to schizophrenia. The span of apprehension task was found to be significantly correlated with a measure of thought disorder that assesses resistance to associative distractors and two neuropsychological tests--the Trail-Making Test from the Halstead-Reitan battery and the Digit Symbol Substitution Test--during the testing session conducted while the subjects were partially recovered.

Serotonergic interhemispheric asymmetry: Neurochemical and pharmaco-EEG evidence ☆

1. Postmortem neurochemical investigations revealed interhemispheric asymmetry in the mediofrontal region of human brain. Significantly higher right hemisphere serotonin metabolite (5HIAA) content as well as increased maximal imipramine binding (IB) were found in the right hemisphere than in the left side. 2. IB did not show a gender difference in the mediofrontal area. However, women had higher IB in the right orbital frontal cortex than did men. 3. In vivo pharmaco-EEG results tend to support the postmortem neurochemical data. Intravenous chlorimipramine resulted in an asymmetric topographic distribution of the P300 auditory evoked potential, peak amplitudes were shifted to the right hemisphere.

Going Beyond: An Adventure- and Recreation-Based Group Intervention Promotes Well-Being and Weight Loss in Schizophrenia:

Objective: To undertake a preliminary study to assess the feasibility of clinical implementation and evaluate the effectiveness of a novel adventure- and recreation-based group intervention in the rehabilitation of individuals with schizophrenia. Methods: In a 2-year, prospective, case–control study, 23 consecutively referred, clinically stabilized schizophrenia patients received the new intervention over an 8-month period; 31 patients on the wait list, considered the control group, received standard clinical care that included some recreational activities. Symptom severity, self-esteem, self-appraised cognitive abilities, and functioning were documented for both groups with standardized rating scales administered at baseline, on completion of treatment, and at 12 months posttreatment. Results: Treatment adherence was 97%, and there were no dropouts. Patients in the study group showed marginal improvement in perceived cognitive abilities and on domain-specific functioning measures but experienced a significant improvement in their self-esteem and global functioning (P < 0.05), as well as a weight loss of over 12 lb. Improvement was sustained over 1 year with further occupational and social gains. Conclusion: In the context of overcoming barriers to providing early intervention for youth and preventing metabolic problems among older adults with schizophrenia, adventure- and recreation-based interventions could play a useful complementary role.

Long-term lithium treatment and the kidney. Interim report on fifty patients.

This is a report on the first part of our study of the effects of long-term lithium treatment on the kidney. Creatinine clearance, maximum urinary osmolality and 24 hour urine volume have been tested in 50 affectively ill patients who have been on long-term lithium for more than one year. These findings have been compared with norms and with values of the same tests from screening prior to lithium, available for most of our patients. No evidence was found for any reduction of glomerular filtration during lithium treatment. Low clearance values found in several patients could be accounted for by their age and their pre-lithium values. Urinary concentration defect appeared frequent but the extent of the impairment is difficult to assess because of the uncertainty about the norms applicable to this group of patients. The concentration defect appeared reversible, at least in part. Polyuria above 3 litres/24 hours was found in 10% of patients. An attempt is made to draw practical conclusions from the preliminary findings.

A Simple and Fast Algorithm for Automatic Suppression of High-Amplitude Artifacts in EEG Data

In this paper we present a simple and fast technique for correcting high amplitude artifacts that contaminate EEG signals. Examples of such artifacts are ocular movement, eye blinks, head movement, etc. Since the measured EEG data can be modeled as a linear combination of brain sources and artifacts, the proposed technique is based on multiplying the observed data matrix by a blocking matrix that has the effect of blocking high amplitude artifacts, while linearly transforming the other sources without any distortion. The advantages of using this technique are: 1) it is relatively fast, so it can be applied in real time, 2) it is completely automatic, and 3) can be successfully applied to signals which fail with ICA-based algorithms.

Clozapine in the treatment of refractory schizophrenia: Canadian policies and clinical guidelines.

Clozapine is an atypical neuroleptic agent that has recently become available in Canada with potential clinical efficacy in the treatment of refractory schizophrenia, and in patients with schizophrenia neurologically intolerant to conventional neuroleptics. Although it causes few extrapyramidal symptoms, the drug has a number of other adverse effects including a risk of agranulocytosis in one to two percent of all patients. Because of this, the use of the drug is permitted only if the white blood count is monitored weekly. The monitoring system, outlined in this article, requires a coordinated effort between clinical staff, pharmacy, laboratory and the Clozaril Support and Assistance Network. Clinical guidelines are proposed, detailing the indications and contraindications for treatment and the pharmacokinetics, dosing, adverse effects, and drug interactions with clozapine. In addition, the economics, government policies and implications for future research are considered. Although there are administrative and clinical difficulties associated with its use, clozapine represents an advance in therapeutic research. Patients and family members will be inquiring about the drug and many deserve a trial. This article aims to inform Canadian mental health professionals about the safe and beneficial use of clozapine.

Using pre-treatment electroencephalography data to predict response to transcranial magnetic stimulation therapy for major depression

We investigate the use of machine learning methods based on the pre-treatment electroencephalograph (EEG) to predict response to repetitive transcranial magnetic stimulation (rTMS), which is a non-pharmacological form of therapy for treating major depressive disorder (MDD). The learning procedure involves the extraction of a large number of candidate features from EEG data, from which a very small subset of most statistically relevant features is selected for further processing. A statistical prediction model based on mixture of factor analysis (MFA) model is constructed from a training set that classifies the respective subject into responder and non-responder classes. A leave-2-out (L2O) cross-validation procedure is used to evaluate the prediction performance. This pilot study involves 27 subjects who received either left high-frequency (HF) active rTMS therapy or simultaneous left HF and right low-frequency active rTMS therapy. Our results indicate that it is possible to predict rTMS treatment efficacy of either treatment modality with a specificity of 83% and a sensitivity of 78%, for a combined accuracy of 80%.

Using pre-treatment EEG data to predict response to SSRI treatment for MDD

The problem of identifying in advance the most effective treatment agent for various psychiatric conditions remains an elusive goal. To address this challenge, we propose a machine learning (ML) methodology to predict the response to a selective serotonin reuptake inhibitor (SSRI) medication in subjects suffering from major depressive disorder (MDD), using pre-treatment electroencephalograph (EEG) measurements. The proposed feature selection technique is a modification of the method of Peng et al [10] that is based on a Kullback-Leibler (KL) distance measure. The classifier was realized as a kernelized partial least squares regression procedure, whose output is the predicted response. A low-dimensional kernelized principal component representation of the feature space was used for the purposes of visualization and clustering analysis. The overall method was evaluated using an 11-fold nested cross-validation procedure for which over 85% average prediction performance is obtained. The results indicate that ML methods hold considerable promise in predicting the efficacy of SSRI antidepressant therapy for major depression.

Diagnosis of psychiatric disorders using EEG data and employing a statistical decision model

An automated diagnosis procedure based on a statistical machine learning methodology using electroencephalograph (EEG) data is proposed for diagnosis of psychiatric illness. First, a large collection of candidate features, mostly consisting of various statistical quantities, are calculated from the subjects EEG. This large set of candidate features is then reduced into a much smaller set of most relevant features using a feature selection procedure. The selected features are then used to evaluate the class likelihoods, through the use of a mixture of factor analysis (MFA) statistical model [7]. In a training set of 207 subjects, including 64 subjects with major depressive disorder (MDD), 40 subjects with chronic schizophrenia, 12 subjects with bipolar depression and 91 normal or healthy subjects, the average correct diagnosis rate attained using the proposed method is over 85%, as determined by various cross-validation experiments. The promise is that, with further development, the proposed methodology could serve as a valuable adjunctive tool for the medical practitioner.

Bioavailability and Side Effects of Different Lithium Carbonate Products

Among the three lithium preparations tested, no significant difference was found in the bioavailability, as expressed in serum and erythrocyte lithium concentrations and urinary lithium output. The side effect reports, however, varied significantly among the types of lithium under study. The slower the absorption of a particular preparation, the fewer the side effects. The results of this study support the view that preference should be given to lithium preparations with slow-release properites, particularly in side-effect-prone subjects.