Network mechanisms of intentional learning

The ability to learn new tasks rapidly is a prominent characteristic of human behaviour. This ability relies on flex- ible cognitive systems that adapt in order to encode temporary programs for processing non-automated tasks. Previous functional imaging studies have revealed distinct roles for the lateral frontal cortices (LFCs) and the ven- tral striatum in intentional learning processes. However, the human LFCs are complex; they house multiple dis- tinct sub-regions, each of which co-activates with a different functional network. It remains unclear how these LFC networks differ in their functions and how they coordinate with each other, and the ventral striatum, to support intentional learning. Here, we apply a suite of fMRI connectivity methods to determine how LFC networks activate and interact at different stages of two novel tasks, in which arbitrary stimulus-response rules are learnt either from explicit instruction or by trial-and-error. We report that the networks activate en masse and in synchrony when novel rules are being learnt from instruction. However, these networks are not homogeneous in their functions; instead, the directed connectivities between them vary asymmetrically across the learning timecourse and they disengage from the task sequentially along a rostro-caudal axis. Furthermore, when negative feedback indicates the need to switch to alternative stimulus–response rules, there is additional input to the LFC networks from the ventral striatum. These results support the hypotheses that LFC networks interact as a hierarchical system during intentional learning and that signals from the ventral striatum have a driving influence on this system when the internal program for processing the task is updated.

Dynamic Network Mechanisms of Relational Integration

A prominent hypothesis states that specialized neural modules within the human lateral frontopolar cortices (LFPCs) support “relational integration” (RI), the solving of complex problems using inter-related rules. However, it has been proposed that LFPC activity during RI could reflect the recruitment of additional “domain-general” resources when processing more difficult problems in general as opposed to RI specifi- cally. Moreover, theoretical research with computational models has demonstrated that RI may be supported by dynamic processes that occur throughout distributed networks of brain regions as opposed to within a discrete computational module. Here, we present fMRI findings from a novel deductive reasoning paradigm that controls for general difficulty while manipulating RI demands. In accordance with the domain- general perspective, we observe an increase in frontoparietal activation during challenging problems in general as opposed to RI specifically. Nonetheless, when examining frontoparietal activity using analyses of phase synchrony and psychophysiological interactions, we observe increased network connectivity during RI alone. Moreover, dynamic causal modeling with Bayesian model selection identifies the LFPC as the effective connectivity source. Based on these results, we propose that during RI an increase in network connectivity and a decrease in network metastability allows rules that are coded throughout working memory systems to be dynamically bound. This change in connectivity state is top-down propagated via a hierarchical system of domain-general networks with the LFPC at the apex. In this manner, the functional network perspective reconciles key propositions of the globalist, modular, and computational accounts of RI within a single unified framework.

Modelos de resposta à interação entre fármacos anestésicos : análise de regressão e análise de Clusters

Os avanços tecnológicos e científicos, na área da saúde, têm vindo a aliar áreas como a Medicina e a Matemática, cabendo à ciência adequar de forma mais eficaz os meios de investigação, diagnóstico, monitorização e terapêutica. Os métodos desenvolvidos e os estudos apresentados nesta dissertação resultam da necessidade de encontrar respostas e soluções para os diferentes desafios identificados na área da anestesia. A índole destes problemas conduz, necessariamente, à aplicação, adaptação e conjugação de diferentes métodos e modelos das diversas áreas da matemática. A capacidade para induzir a anestesia em pacientes, de forma segura e confiável, conduz a uma enorme variedade de situações que devem ser levadas em conta, exigindo, por isso, intensivos estudos. Assim, métodos e modelos de previsão, que permitam uma melhor personalização da dosagem a administrar ao paciente e por monitorizar, o efeito induzido pela administração de cada fármaco, com sinais mais fiáveis, são fundamentais para a investigação e progresso neste campo. Neste contexto, com o objetivo de clarificar a utilização em estudos na área da anestesia de um ajustado tratamento estatístico, proponho-me abordar diferentes análises estatísticas para desenvolver um modelo de previsão sobre a resposta cerebral a dois fármacos durante sedação. Dados obtidos de voluntários serão utilizados para estudar a interação farmacodinâmica entre dois fármacos anestésicos. Numa primeira fase são explorados modelos de regressão lineares que permitam modelar o efeito dos fármacos no sinal cerebral BIS (índice bispectral do EEG – indicador da profundidade de anestesia); ou seja estimar o efeito que as concentrações de fármacos têm na depressão do eletroencefalograma (avaliada pelo BIS). Na segunda fase deste trabalho, pretende-se a identificação de diferentes interações com Análise de Clusters bem como a validação do respetivo modelo com Análise Discriminante, identificando grupos homogéneos na amostra obtida através das técnicas de agrupamento. O número de grupos existentes na amostra foi, numa fase exploratória, obtido pelas técnicas de agrupamento hierárquicas, e a caracterização dos grupos identificados foi obtida pelas técnicas de agrupamento k-means. A reprodutibilidade dos modelos de agrupamento obtidos foi testada através da análise discriminante. As principais conclusões apontam que o teste de significância da equação de Regressão Linear indicou que o modelo é altamente significativo. As variáveis propofol e remifentanil influenciam significativamente o BIS e o modelo melhora com a inclusão do remifentanil. Este trabalho demonstra ainda ser possível construir um modelo que permite agrupar as concentrações dos fármacos, com base no efeito no sinal cerebral BIS, com o apoio de técnicas de agrupamento e discriminantes. Os resultados desmontram claramente a interacção farmacodinâmica dos dois fármacos, quando analisamos o Cluster 1 e o Cluster 3. Para concentrações semelhantes de propofol o efeito no BIS é claramente diferente dependendo da grandeza da concentração de remifentanil. Em suma, o estudo demostra claramente, que quando o remifentanil é administrado com o propofol (um hipnótico) o efeito deste último é potenciado, levando o sinal BIS a valores bastante baixos.

O papel do poema «Correspondances» no Teatro de Vanguarda dos séculos XIX e XX

Ensaio produzido no quadro do Colóquio Internacional "Baudelaire (1821-867) e as Posteridades do Moderno", organizado por Jorge Fazenda Lourenço, Faculdade de Ciências Humanas, Universidade Católica Portuguesa, 2007.

Nonlinear dynamics of the patient’s response to drug effect during general anesthesia

In today’s healthcare paradigm, optimal sedation during anesthesia plays an important role both in patient welfare and in the socio-economic context. For the closed-loop control of general anesthesia, two drugs have proven to have stable, rapid onset times: propofol and remifentanil. These drugs are related to their effect in the bispectral index, a measure of EEG signal. In this paper wavelet time–frequency analysis is used to extract useful information from the clinical signals, since they are time-varying and mark important changes in patient’s response to drug dose. Model based predictive control algorithms are employed to regulate the depth of sedation by manipulating these two drugs. The results of identification from real data and the simulation of the closed loop control performance suggest that the proposed approach can bring an improvement of 9% in overall robustness and may be suitable for clinical practice.

Nonlinear dynamics of the patient’s response to drug effect during general anesthesia

In today’s healthcare paradigm, optimal sedation during anesthesia plays an important role both in patient welfare and in the socio-economic context. For the closed-loop control of general anesthesia, two drugs have proven to have stable, rapid onset times: propofol and remifentanil. These drugs are related to their effect in the bispectral index, a measure of EEG signal. In this paper wavelet time–frequency analysis is used to extract useful information from the clinical signals, since they are time-varying and mark important changes in patient’s response to drug dose. Model based predictive control algorithms are employed to regulate the depth of sedation by manipulating these two drugs. The results of identification from real data and the simulation of the closed loop control performance suggest that the proposed approach can bring an improvement of 9% in overall robustness and may be suitable for clinical practice.

Long-term outcome after cognitive and behavioral regression in nonlesional epilepsy with continuous spike-waves during slow-wave sleep.

PURPOSE: To present the long-term follow-up of 10 adolescents and young adults with documented cognitive and behavioral regression as children due to nonlesional focal, mainly frontal, epilepsy with continuous spike-waves during slow wave sleep (CSWS). METHODS: Past medical and electroencephalography (EEG) data were reviewed and neuropsychological tests exploring main cognitive functions were administered. KEY FINDINGS: After a mean duration of follow-up of 15.6 years (range, 8-23 years), none of the 10 patients had recovered fully, but four regained borderline to normal intelligence and were almost independent. Patients with prolonged global intellectual regression had the worst outcome, whereas those with more specific and short-lived deficits recovered best. The marked behavioral disorders resolved in all but one patient. Executive functions were neither severely nor homogenously affected. Three patients with a frontal syndrome during the active phase (AP) disclosed only mild residual executive and social cognition deficits. The main cognitive gains occurred shortly after the AP, but qualitative improvements continued to occur. Long-term outcome correlated best with duration of CSWS. SIGNIFICANCE: Our findings emphasize that cognitive recovery after cessation of CSWS depends on the severity and duration of the initial regression. None of our patients had major executive and social cognition deficits with preserved intelligence, as reported in adults with early destructive lesions of the frontal lobes. Early recognition of epilepsy with CSWS and rapid introduction of effective therapy are crucial for a best possible outcome.

Properties of functional brain networks correlate with frequency of psychogenic non-epileptic seizures.

Abnormalities in the topology of brain networks may be an important feature and etiological factor for psychogenic non-epileptic seizures (PNES). To explore this possibility, we applied a graph theoretical approach to functional networks based on resting state EEGs from 13 PNES patients and 13 age- and gender-matched controls. The networks were extracted from Laplacian-transformed time-series by a cross-correlation method. PNES patients showed close to normal local and global connectivity and small-world structure, estimated with clustering coefficient, modularity, global efficiency, and small-worldness (SW) metrics, respectively. Yet the number of PNES attacks per month correlated with a weakness of local connectedness and a skewed balance between local and global connectedness quantified with SW, all in EEG alpha band. In beta band, patients demonstrated above-normal resiliency, measured with assortativity coefficient, which also correlated with the frequency of PNES attacks. This interictal EEG phenotype may help improve differentiation between PNES and epilepsy. The results also suggest that local connectivity could be a target for therapeutic interventions in PNES. Selective modulation (strengthening) of local connectivity might improve the skewed balance between local and global connectivity and so prevent PNES events.

Quantifying consistency of Event Related Potentials across subjects based on single-trial topographic analysis

Introduction: Non-invasive brain imaging techniques often contrast experimental conditions across a cohort of participants, obfuscating distinctions in individual performance and brain mechanisms that are better characterised by the inter-trial variability. To overcome such limitations, we developed topographic analysis methods for single-trial EEG data [1]. So far this was typically based on time-frequency analysis of single-electrode data or single independent components. The method's efficacy is demonstrated for event-related responses to environmental sounds, hitherto studied at an average event-related potential (ERP) level. Methods: Nine healthy subjects participated to the experiment. Auditory meaningful sounds of common objects were used for a target detection task [2]. On each block, subjects were asked to discriminate target sounds, which were living or man-made auditory objects. Continuous 64-channel EEG was acquired during the task. Two datasets were considered for each subject including single-trial of the two conditions, living and man-made. The analysis comprised two steps. In the first part, a mixture of Gaussians analysis [3] provided representative topographies for each subject. In the second step, conditional probabilities for each Gaussian provided statistical inference on the structure of these topographies across trials, time, and experimental conditions. Similar analysis was conducted at group-level. Results: Results show that the occurrence of each map is structured in time and consistent across trials both at the single-subject and at group level. Conducting separate analyses of ERPs at single-subject and group levels, we could quantify the consistency of identified topographies and their time course of activation within and across participants as well as experimental conditions. A general agreement was found with previous analysis at average ERP level. Conclusions: This novel approach to single-trial analysis promises to have impact on several domains. In clinical research, it gives the possibility to statistically evaluate single-subject data, an essential tool for analysing patients with specific deficits and impairments and their deviation from normative standards. In cognitive neuroscience, it provides a novel tool for understanding behaviour and brain activity interdependencies at both single-subject and at group levels. In basic neurophysiology, it provides a new representation of ERPs and promises to cast light on the mechanisms of its generation and inter-individual variability.

Ecology and neurophysiology of sleep in two wild sloth species

Study Objectives: Interspecific variation in sleep measured in captivity correlates with various physiological and environmental factors, including estimates of predation risk in the wild. However, it remains unclear whether prior comparative studies have been confounded by the captive recording environment. Herein we examine the impact of predation pressure on sleep in sloths living in the wild. Design: Comparison of two closely related sloth species, one exposed to predation and one free from predation. Setting: Panamanian mainland rainforest (predators present) and island mangrove (predators absent). Participants: Mainland (Bradypus variegatus, 5 males and 4 females) and island (Bradypus pygmaeus, 6 males) sloths. Interventions: None. Measurements and Results: EEG and EMG activity were recorded using a miniature data logger. Although both species spent between 9 and 10 hours per day sleeping, the mainland sloths showed a preference for sleeping at night, whereas island sloths showed no preference for sleeping during the day or night. EEG activity during NREM sleep showed lower low-frequency power, and increased spindle and higher frequency power in island sloths when compared to mainland sloths. Conclusions: In sloths sleeping in the wild, predation pressure influenced the timing of sleep, but not the amount of time spent asleep. The preference for sleeping at night in mainland sloths may be a strategy to avoid detection by nocturnal cats. The pronounced differences in the NREM sleep EEG spectrum remain unexplained, but might be related to genetic or environmental factors.

Status epilepticus in fragile X syndrome.

Epilepsy is frequent in fragile X syndrome (FXS), the most common cause of inherited mental retardation. Status epilepticus (SE), however, seems exceptional in FXS, particularly as an initial epileptic manifestation. To our knowledge, SE was reported in only four FXS patients. We report the clinical features and electroencephalography (EEG) findings of five children with FXS, who presented with SE as their initial seizure.

Sustaining sleep spindles through enhanced SK2-channel activity consolidates sleep and elevates arousal threshold.

Sleep spindles are synchronized 11-15 Hz electroencephalographic (EEG) oscillations predominant during nonrapid-eye-movement sleep (NREMS). Rhythmic bursting in the reticular thalamic nucleus (nRt), arising from interplay between Ca(v)3.3-type Ca(2+) channels and Ca(2+)-dependent small-conductance-type 2 (SK2) K(+) channels, underlies spindle generation. Correlative evidence indicates that spindles contribute to memory consolidation and protection against environmental noise in human NREMS. Here, we describe a molecular mechanism through which spindle power is selectively extended and we probed the actions of intensified spindling in the naturally sleeping mouse. Using electrophysiological recordings in acute brain slices from SK2 channel-overexpressing (SK2-OE) mice, we found that nRt bursting was potentiated and thalamic circuit oscillations were prolonged. Moreover, nRt cells showed greater resilience to transit from burst to tonic discharge in response to gradual depolarization, mimicking transitions out of NREMS. Compared with wild-type littermates, chronic EEG recordings of SK2-OE mice contained less fragmented NREMS, while the NREMS EEG power spectrum was conserved. Furthermore, EEG spindle activity was prolonged at NREMS exit. Finally, when exposed to white noise, SK2-OE mice needed stronger stimuli to arouse. Increased nRt bursting thus strengthens spindles and improves sleep quality through mechanisms independent of EEG slow waves (<4 Hz), suggesting SK2 signaling as a new potential therapeutic target for sleep disorders and for neuropsychiatric diseases accompanied by weakened sleep spindles.

Prognostication after cardiac arrest and hypothermia: a prospective study.

Current American Academy of Neurology (AAN) guidelines for outcome prediction in comatose survivors of cardiac arrest (CA) have been validated before the therapeutic hypothermia era (TH). We undertook this study to verify the prognostic value of clinical and electrophysiological variables in the TH setting. A total of 111 consecutive comatose survivors of CA treated with TH were prospectively studied over a 3-year period. Neurological examination, electroencephalography (EEG), and somatosensory evoked potentials (SSEP) were performed immediately after TH, at normothermia and off sedation. Neurological recovery was assessed at 3 to 6 months, using Cerebral Performance Categories (CPC). Three clinical variables, assessed within 72 hours after CA, showed higher false-positive mortality predictions as compared with the AAN guidelines: incomplete brainstem reflexes recovery (4% vs 0%), myoclonus (7% vs 0%), and absent motor response to pain (24% vs 0%). Furthermore, unreactive EEG background was incompatible with good long-term neurological recovery (CPC 1-2) and strongly associated with in-hospital mortality (adjusted odds ratio for death, 15.4; 95% confidence interval, 3.3-71.9). The presence of at least 2 independent predictors out of 4 (incomplete brainstem reflexes, myoclonus, unreactive EEG, and absent cortical SSEP) accurately predicted poor long-term neurological recovery (positive predictive value = 1.00); EEG reactivity significantly improved the prognostication. Our data show that TH may modify outcome prediction after CA, implying that some clinical features should be interpreted with more caution in this setting as compared with the AAN guidelines. EEG background reactivity is useful in determining the prognosis after CA treated with TH.

Controlled study of 50-Hz repetitive transcranial magnetic stimulation for the treatment of Parkinson disease.

OBJECTIVE: To investigate the safety and efficacy of 50-Hz repetitive transcranial magnetic stimulation (rTMS) in the treatment of motor symptoms in Parkinson disease (PD). BACKGROUND: Progression of PD is characterized by the emergence of motor deficits that gradually respond less to dopaminergic therapy. rTMS has shown promising results in improving gait, a major cause of disability, and may provide a therapeutic alternative. Prior controlled studies suggest that an increase in stimulation frequency might enhance therapeutic efficacy. METHODS: In this randomized, double blind, sham-controlled study, the authors investigated the safety and efficacy of 50-Hz rTMS of the motor cortices in 8 sessions over 2 weeks. Assessment of safety and clinical efficacy over a 1-month period included timed tests of gait and bradykinesia, Unified Parkinson's Disease Rating Scale (UPDRS), and additional clinical, neurophysiological, and neuropsychological parameters. In addition, the safety of 50-Hz rTMS was tested with electromyography-electroencephalogram (EMG-EEG) monitoring during and after stimulation. RESULTS: The authors investigated 26 patients with mild to moderate PD: 13 received 50-Hz rTMS and 13 sham stimulation. The 50-Hz rTMS did not improve gait, bradykinesia, and global and motor UPDRS, but there appeared a short-lived "on"-state improvement in activities of daily living (UPDRS II). The 50-Hz rTMS lengthened the cortical silent period, but other neurophysiological and neuropsychological measures remained unchanged. EMG/EEG recorded no pathological increase of cortical excitability or epileptic activity. There were no adverse effects. CONCLUSION: It appears that 50-Hz rTMS of the motor cortices is safe, but it fails to improve motor performance and functional status in PD. Prolonged stimulation or other techniques with rTMS might be more efficacious but need to be established in future research.

Successful surgical resection in non-lesional operculo-insular epilepsy without intracranial monitoring.

Pre-operative assessment and surgical management of patients with non-lesional extratemporal epilepsy remain challenging due to a lack of precise localisation of the epileptic zone. In most cases, invasive recording with depth or subdural electrodes is required. Here, we describe the case of 6.5-year-old girl who underwent comprehensive non-invasive phase I video-EEG investigation for drug-resistant epilepsy, including electric source and nuclear imaging. Left operculo-insular epilepsy was diagnosed. Post-operatively, she developed aphasia which resolved within one year, corroborating the notion of enhanced language plasticity in children. The patient remained seizure-free for more than three years.