Language plasticity revealed by electroencephalogram mapping

Brain entropy and neurotrophic molecular markers accompanying clinical improvement after ketamine: Preliminary evidence in adolescents with treatment-resistant depression

BACKGROUND

Current theory suggests that treatment-resistant depression (TRD) involves impaired neuroplasticity resulting in cognitive and neural rigidity, and that clinical improvement may require increasing brain flexibility and adaptability.

AIMS

In this hypothesis-generating study, we sought to identify preliminary evidence of brain flexibility correlates of clinical change within the context of an open-label ketamine trial in adolescents with TRD, focusing on two promising candidate markers of neural flexibility: (a) entropy of resting-state functional magnetic resonance imaging (fMRI) signals; and (b) insulin-stimulated phosphorylation of mammalian target of rapamycin (mTOR) and glycogen synthase-3-beta (GSK3β) in peripheral blood mononuclear cells.

METHODS

We collected resting-state functional magnetic resonance imaging data and blood samples from 13 adolescents with TRD before and after a series of six ketamine infusions over 2 weeks. Usable pre/post ketamine data were available from 11 adolescents for imaging and from 10 adolescents for molecular signaling. We examined correlations between treatment response and changes in the central and peripheral flexibility markers.

RESULTS

Depression reduction correlated with increased nucleus accumbens entropy. Follow-up analyses suggested that physiological changes were associated with treatment response. In contrast to treatment non-responders (n=6), responders (n=5) showed greater increase in nucleus accumbens entropy after ketamine, together with greater post-treatment insulin/mTOR/GSK3β signaling.

CONCLUSIONS

These data provide preliminary evidence that changes in neural flexibility may underlie symptom relief in adolescents with TRD following ketamine. Future research with adequately powered samples is needed to confirm resting-state entropy and insulin-stimulated mTOR and GSK3β as brain flexibility markers and candidate targets for future clinical trials.

CLINICAL TRIAL NAME

Ketamine in adolescents with treatment-resistant depressionURL: https://clinicaltrials.gov/ct2/show/NCT02078817Registration number: NCT02078817.

Combining Different Tools for EEG Analysis to Study the Distributed Character of Language Processing

Recent studies on language processing indicate that language cognition is better understood if assumed to be supported by a distributed intelligent processing system enrolling neurons located all over the cortex, in contrast to reductionism that proposes to localize cognitive functions to specific cortical structures. Here, brain activity was recorded using electroencephalogram while volunteers were listening or reading small texts and had to select pictures that translate meaning of these texts. Several techniques for EEG analysis were used to show this distributed character of neuronal enrollment associated with the comprehension of oral and written descriptive texts. Low Resolution Tomography identified the many different sets (s_i) of neurons activated in several distinct cortical areas by text understanding. Linear correlation was used to calculate the information H(e_i) provided by each electrode of the 10/20 system about the identified s_i. H(e_i) Principal Component Analysis (PCA) was used to study the temporal and spatial activation of these sources s_i. This analysis evidenced 4 different patterns of H(e_i) covariation that are generated by neurons located at different cortical locations. These results clearly show that the distributed character of language processing is clearly evidenced by combining available EEG technologies.

Brain activity and medical diagnosis: an EEG study

Background

Despite new brain imaging techniques that have improved the study of the underlying processes of human decision-making, to the best of our knowledge, there have been very few studies that have attempted to investigate brain activity during medical diagnostic processing. We investigated brain electroencephalography (EEG) activity associated with diagnostic decision-making in the realm of veterinary medicine using X-rays as a fundamental auxiliary test. EEG signals were analysed using Principal Components (PCA) and Logistic Regression Analysis

Results

The principal component analysis revealed three patterns that accounted for 85% of the total variance in the EEG activity recorded while veterinary doctors read a clinical history, examined an X-ray image pertinent to a medical case, and selected among alternative diagnostic hypotheses. Two of these patterns are proposed to be associated with visual processing and the executive control of the task. The other two patterns are proposed to be related to the reasoning process that occurs during diagnostic decision-making.

Conclusions

PCA analysis was successful in disclosing the different patterns of brain activity associated with hypothesis triggering and handling (pattern P₁); identification uncertainty and prevalence assessment (pattern P₃), and hypothesis plausibility calculation (pattern P₂); Logistic regression analysis was successful in disclosing the brain activity associated with clinical reasoning success, and together with regression analysis showed that clinical practice reorganizes the neural circuits supporting clinical reasoning.

Neurodynamics of an election

Variables influencing decision-making in real settings, as in the case of voting decisions, are uncontrollable and in many times even unknown to the experimenter. In this case, the experimenter has to study the intention to decide (vote) as close as possible in time to the moment of the real decision (election day). Here, we investigated the brain activity associated with the voting intention declared 1 week before the election day of the Brazilian Firearms Control Referendum about prohibiting the commerce of firearms. Two alliances arose in the Congress to run the campaigns for YES (for the prohibition of firearm commerce) and NO (against the prohibition of firearm commerce) voting. Time constraints imposed by the necessity of studying a reasonable number (here, 32) of voters during a very short time (5 days) made the EEG the tool of choice for recording the brain activity associated with voting decision. Recent fMRI and EEG studies have shown decision-making as a process due to the enrollment of defined neuronal networks. In this work, a special EEG technique is applied to study the topology of the voting decision-making networks and is compared to the results of standard ERP procedures. The results show that voting decision-making enrolled networks in charge of calculating the benefits and risks of the decision of prohibiting or allowing firearm commerce and that the topology of such networks was vote- (i.e., YES/NO-) sensitive.

Long-term cognitive outcome of hemiconvulsion-hemiplegia-epilepsy syndrome affecting the left cerebral hemisphere

Long-term cognitive outcome following hemiconvulsion-hemiplegia-epilepsy (HHE) syndrome has been poorly studied, with little attention to the implications of side of involvement in HHE. This retrospective study describes language lateralization and cognitive performance in five patients with HHE syndrome affecting the left cerebral hemisphere. All of the patients had to have intracarotid sodium amytal testing (IAT) to be included in this study. The mean age of the patients was 30.2 years (range: 13-50). All patients had their hemiconvulsive seizures before age 1(1/2) years (range: 6-13 months). All patients had right-sided hemiatrophy of the body, left mesial temporal sclerosis, and seizures originating from the left temporal lobe. The habitual seizures began at a mean age of 4.5 years (range: 1.5-12 years). Performance on tests of intelligence, verbal memory, and visual memory was examined. Language was represented in the right cerebral hemisphere in three patients, the left hemisphere in one patient, and both hemispheres with predominance on the right side in the fifth patient. Intellectual functioning was in the borderline to extremely low range among the patients with right hemispheric or bilateral representation for language. These patients were variably impaired on measures of verbal and visual memory. The patient with left hemispheric representation for language performed in the average range on tests of intellectual functioning and verbal memory, whereas scores on visual memory were variable. This study demonstrated that reorganization of language to the right cerebral hemisphere or its bilateral representation is common in patients with HHE syndrome affecting the left cerebral hemisphere, and is associated with poor cognitive outcome.

Model based prognosis of postoperative object naming in left temporal lobe epilepsy

Epilepsy surgery in the left temporal lobe is associated with a high risk of naming decline. In the present study, in 45 patients with left temporal lobe epilepsy (TLE) and confirmed left hemisphere language dominance, 13 (29%) patients demonstrated postoperative decrement >or=5 naming failures in the Boston Naming Test (BNT). Multivariate discriminant analysis with age at onset of epilepsy, age at first risk, age at operation and preoperative naming performance as predictors indicated that 12 (92%) patients with later naming decline could be identified preoperatively. Univariate group comparisons revealed that specifically patients with seizure onset later than 14 years without preceding risk factors (e.g., febrile seizures) are in danger of postoperative dysnomia. It is hypothesized, that there is a strong connection between stable naming performance and deviant intrahemispheric speech representation as a result of early brain damage and/or chronic seizures.

Brain mappings of the arithmetic processing in children and adults

Despite the increasing number of experimental mapping showing that human arithmetic cognition is supported by widely spread neural circuits; the theoretical reasoning about these data remains mostly metaphorical and guided by a connectionist approach. Although neurons at distinct areas in the brain are assumed to take charge of different duties in the solution of the experimental task, the results are always discussed by hypothesizing some association between the different areas without questioning any difference of behavior at the level of the neurons at each of these areas. Here, the brain is assumed as Distributed Intelligent Processing System (DIPS) formed by collections of loosely interacting specialized agents (neurons), each agent specializing, for example, in data collection (sensors), problem solving (associative neurons), data communication (interneuronal systems) and in acting upon the surrounding environment (motorneurons). A new technique for EEG brain mapping is proposed and used to study arithmetic cognition in elementary school aged children and adults. Factor analysis showed three distinct patterns of neuronal recruitment for arithmetic calculations in all experimental groups which varied according to the type of calculation, age and sex.

Proton magnetic resonance spectroscopy improves outcome prediction in perinatal CNS insults

OBJECTIVE

Prediction of neurologic outcome is difficult in neonates with acute nervous system injury. Previous studies using proton magnetic resonance spectroscopy ((1)H-MRS) have been used to predict short-term neurologic outcome in neonates with a variety of neurologic insults. We were interested in determining the effectiveness of combining clinical evaluation and spectroscopy obtained at the time of injury in predicting neurologic outcome at 24 months.

STUDY DESIGN

We studied 33 neonates with acute central nervous system injury, 5.8+/-3.7 days of injury, owing to hypoxic-ischemic encephalopathy. Neonates were assessed using clinical variables (initial arterial pH, initial blood glucose, Sarnat score, electroencephalography) and spectroscopy (NAA/Cho, NAA/Cre, Cho/Cre, and lactate). Neonates were divided into two outcome groups: good/moderate and poor. Differences between the groups were assessed using chi(2) and t-test analyses. We analyzed the best predictors of outcome using discriminant analysis and calculated sensitivity, specificity, positive, and negative predictive values for each variable independently and in combination.

RESULTS

There were significant differences between the good/moderate and poor outcome for the Sarnat score, EEG, lactate, and NAA/Cho. Spectroscopy combined with clinical variables improved sensitivity, but not specificity for predicting outcome. The presence of lactate had the best individual predictive value. Combination of the clinical with the MRS variables had the highest predictive value.

CONCLUSION

Proton magnetic resonance spectroscopy done early after injury improves the ability to predict neurologic outcome at 24 months of age.