The gate control theory of pain proposed by Melzack and Wall in 1965 is revisited through two mechanisms of neuronal regulation: NMDA synaptic plasticity and intrinsic plasticity. The Melzack and Wall circuit was slightly modified by using strictly excitatory nociceptive afferents (in the original arrangement, nociceptive afferents were considered excitatory when they project to central transmission neurons and inhibitory when projecting to substantia gelatinosa). The results of our neurocomputational model are consistent with biological ones in that nociceptive signals are blocked on their way to the brain every time a tactile stimulus is given at the same locus where the pain was produced. In the computational model, the whole set of parameters, independently of their initialization, always converge to the correct values to allow the correct computation of the circuit. To test the model, other painful conditions were analyzed: phantom limb pain, wind-up and wind-down pain, breakthrough pain, and demyelinating syndromes like Guillain-Barré and multiple sclerosis.

In this paper, we use the neural property known as intrinsic plasticity to develop neural network models that resemble the koniocortex, the fourth layer of sensory cortices. These models evolved from a very basic two-layered neural network to a complex associative koniocortex network. In the initial network, intrinsic and synaptic plasticity govern the shifting of the activation function, and the modification of synaptic weights, respectively. In this first version, competition is forced, so that the most activated neuron is arbitrarily set to one and the others to zero, while in the second, competition occurs naturally due to inhibition between second layer neurons. In the third version of the network, whose architecture is similar to the koniocortex, competition also occurs naturally owing to the interplay between inhibitory interneurons and synaptic and intrinsic plasticity. A more complex associative neural network was developed based on this basic koniocortex-like neural network, capable of dealing with incomplete patterns and ideally suited to operating similarly to a learning vector quantization network. We also discuss the biological plausibility of the networks and their role in a more complex thalamocortical model.

Several research studies point to the fact that sensory and cognitive reductions like cataracts, deafness, macular degeneration, or even lack of activity after job retirement, precede the onset of Alzheimer’s disease. To simulate Alzheimer’s disease earlier stages, which manifest in sensory cortices, we used a computational model of the koniocortex that is the first cortical stage processing sensory information. The architecture and physiology of the modeled koniocortex resemble those of its cerebral counterpart being capable of continuous learning. This model allows one to analyze the initial phases of Alzheimer’s disease by “aging” the artificial koniocortex through synaptic pruning, by the modification of acetylcholine and GABA-A signaling, and by reducing sensory stimuli, among other processes. The computational model shows that during aging, a GABA-A deficit followed by a reduction in sensory stimuli leads to a dysregulation of neural excitability, which in the biological brain is associated with hypermetabolism, one of the earliest symptoms of Alzheimer’s disease.

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Introduction: Patients' compliance to illicit drugs addiction´s treatment, is a limiting factor for the effectiveness of these patients' treatment. Objective: The aim of this research was to study the pharmacological therapy and its side effects, in patients undergoing addiction treatment. Results: This study selected 31 patients with mean age of 33,61± 1,90 years old enrolled in a public mental health service with psychotic disorder related to the use of cocaine, crack an alcohol. Patients under this study were addicted to alcohol (61,29%), cocaine, crack or the association of both (38,71%). Effects related to the use of cocaine were delirium/hallucination (50%), cardiovascular effects (27,76%), psychomotor agitation (11,12%). (No effects reported 11,10%). Patient-reported, crack-related effects were delirium and hallucination (50%), cardiovascular effects (37,50%). (No effects reported 12,50%). Psychosis (73,08%), aggressive behavior (7,69%), abstinence syndrome (11,54%), were associated to the use of alcohol. (No side effects reported 7,69%) The pharmacological treatment to these patients were typical neuroleptics (41,94%), atypical neuroleptics (22,58%), typical and atypical neuroleptics associated (29,03%), (No treatment 6,45%). Side effects related to pharmacological treatment were extrapyramidal effects (56,24%), delirium/hallucination (43,74%), memory impairment (34,37%), anxiety(31,25%),attention deficit (21,87%), psychotic depression (12,50%), verbal communication deficit (3,12%). These effects were treated with biperiden (58,34%), promethazine or benzodiazepines (25,00%). (No treatment was done in16,67%). Conclusions: The use of neuroleptics in the treatment of psychotic disorders due to the use of illicit drugs should be evaluated. The side effects related to the neuroleptics must be carefully controlled in order to guarantee the patientsć ompliance to the treatment.

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IntroductionExtrapyramidal side-effects (EPS) related to the use of neuroleptics are an limiting factor to patients’ compliance during the treatment with this group of drugs.ObjectiveThe aim of this study was to identify which drugs are mostly prescribed for cocaine, crack and alcohol addicts’ psychotic symptoms.MethodsThis study selected 31 patients with mean age of 33.61 ± 1.90 enrolled with psychotic disorders related to use of illicit drugs in an public mental health service.ResultsPatients under this study were addict to alcohol (61,29%), cocaine or crack, associated (38,71%).The percentage of patients addicted to alcohol treated with typical neuroleptic-(typical-neurol) was 42,11%, with atypical neuroleptic-(atypical-neurol) was 26,32%, with association of typical and atypical neuroleptics-(typical/atypical-neurol) (21,60%), and with benzodiazepines associated with serotonin-reuptake-inhibitors (BZD-SSRI) (10,00)%. The cocaine or crack associated or not with alcohol patients were treated with typical-neurol (41,67%), atypical-neurol (41,67%), typical/atypical-neurolol (8,33%) and BZD-SSRI (8,33%).The EPS related to the use of neuroleptics in patients addicted to alcohol were given biperiden (52,65%), promethazine or anticolvulsant (Prometh/Anticonv) (42,11%) and no-treatment (5,26%). For those patients, addicted to cocaine, crack and alcohol altogether were given biperiden (58,34%), Prometh/Anticonv (25,00%) and no-treatment (16,67%).ConclusionsIn the case of using neuroleptics, the EPS should be reversed with biperiden in an dose combined with the neuroleptic prescribed to each individual, in an effort to minimized hallucination. Also, if sedation was indicated using Prometh/Anticonv to patients that are taking neuroleptics, then the health care professional team in charge must be aware of consciousness level-reduction.

Resumo -O homem é o reflexo de suas experiências pessoais. Todo o conhecimento adquirido em sua existência é armazenado em suas memórias e possibilita agir, decidir e aprimorar suas características ao longo de sua vida. São essas memórias que o tornam um ser humano único. Os processos e sistemas envolvidos na formação e recuperação das memórias vêm sendo investigados e compreendidos. Não se sabe ao certo como o cérebro classifica as informações em padrões quando os estímulos são apresentados em conjunto com novas informações ou inseridos em contextos desconhecidos. Este trabalho tem por objetivo apresentar um simulador computacional baseado em técnicas de Redes Neurais Artificiais para estudo das estratégias categóricas de formação de conceitos e recordação, tornando-se um instrumento de pesquisa, avaliação e ensaio sobre esses processos. A criação de uma ferramenta computacional voltada para a experimentação de processos de memorização possui uma forte demanda por parte dos pesquisadores da area biológica por possibilitar testes de hipóteses e abordagens anteriores e preparatórios ao experimento real com pessoas, que necessita de observação criteriosa de condutas, procedimentos e legislação pertinentes. O desafio maior deste trabalho foi traduzir o conhecimento biológico, normalmente descrito em linguagem natural, para uma linguagem implementável computacionalmente, além de encontrar as características e funcionalidades ideais para serem representativas dos processos em estudo. Palavras-chaves - IntroduçãoA personalidade humana é fruto das memórias. São as memórias que caracterizam um indivíduo e o discernem de outro, mesmo quando se compara gêmeos univitelinos (geneticamente iguais). Isto é, suas ações, reações e atitudes perante fatos e acontecimentos da vida são reflexo de suas memórias, estejam elas conscientes ou não. A cada nova experiência, ajustes e reconsiderações são realizados, levando a uma reconstrução das memórias previamente arquivadas. Mesmo fatos supostamente esquecidos, ou julgados perdidos em decorrência da passagem do tempo, traduzem-se na personalidade. Muitas vezes, os mecanismos cerebrais "suprimem" a lembrança de fatos ou acontecimentos por seu conteúdo desagradável, como se houvesse um esforço no sentido de preservar o organismo dessas recordações; mas esses conteúdos continuam a influenciar as decisões dos indivíduos [1].A representação de informações conceituais pelos sistemas de memória é objeto de estudo de áreas da ciência como a Psicologia, a Neuropsicologia e a Neurociências.Várias teorias sobre o tema podem ser encontradas em trabalhos científicos, como a teoria de rede semântica, da profundidade de processamento, do processamento automático e controlado, entre outros. São também variadas as descrições de estratégias de memorização destas informações processadas, sendo esta capacidade atribuída à memória operacional e de longa duração.Em crianças observam-se diferentes estratégias na manipulação de categorias e também na memorização em função da faixa etária e nível de instruçã...