Interest in the hippocampal formation and its role in navigation and memory arose in the second part of the 20th century, at least in part due to the curious case of Henry G. Molaison, who underwent brain surgery for intractable epilepsy. The temporal association observed between the removal of his entorhinal cortex along with a significant part of hippocampus and the developing severe memory deficit inspired scientists to focus on these regions. The subsequent discovery of the so-called place cells in the hippocampus launched the description of many other functional cell types and neuronal networks throughout the Papez-circuit that has a key role in memory processes and spatial information coding (speed, head direction, border, grid, object-vector etc). Each of these cell types has its own unique characteristics, and together they form the so-called “Brain GPS”. The aim of this short survey is to highlight for practicing neurologists the types of cells and neuronal networks that represent the anatomical substrates and physiological correlates of pathological entities affecting the limbic system, especially in the temporal lobe. For that purpose, we survey early discoveries along with the most relevant neuroscience observations from the recent literature. By this brief survey, we highlight main cell types in the hippocampal formation, and describe their roles in spatial navigation and memory processes. In recent decades, an array of new and functionally unique neuron types has been recognized in the hippocampal formation, but likely more remain to be discovered. For a better understanding of the heterogeneous presentations of neurological disorders affecting this anatomical region, insights into the constantly evolving neuroscience behind may be helpful. The public health consequences of diseases that affect memory and spatial navigation are high, and grow as the population ages, prompting scientist to focus on further exploring this brain region.

[What has Go to do with making clinical decisions? One of the greatest intellectual challenges of bedside medicine is making decisions under uncertainty. Besides the psychological traps of traditionally intuitive and heuristic medical decision making, lack of information, scarce resources and characteristics of doctor-patient relationship contribute equally to this uncertainty. Formal, mathematical model based analysis of decisions used widely in developing clinical guidelines and in health technology assessment provides a good tool in theoretical terms to avoid pitfalls of intuitive decision making. Nevertheless it can be hardly used in individual situations and most physicians dislike it as well. This method, however, has its own limitations, especially while tailoring individual decisions, under inclusion of potential lack of input data used for calculations, or its large imprecision, and the low capability of the current mathematical models to represent the full complexity and variability of processes in complex systems. Nevertheless, clinical decision support systems can be helpful in the individual decision making of physicians if they are well integrated in the health information systems, and do not break down the physicians’ autonomy of making decisions. Classical decision support systems are knowledge based and rely on system of rules and problem specific algorithms. They are utilized widely from health administration to image processing. The current information revolution created the so-called artificial intelligence by machine learning methods, i.e. machines can learn indeed. This new generation of artificial intelligence is not based on particular system of rules but on neuronal networks teaching themselves by huge databases and general learning algorithms. This type of artificial intelligence outperforms humans already in certain fields like chess, Go, or aerial combat. Its development is full of challenges and threats, while it presents a technological breakthrough, which cannot be stopped and will transform our world. Its development and application has already started also in the healthcare. Health professionals must participate in this development to steer it into the right direction. Lee Sedol, 18-times Go world champion retired three years after his historical defeat from AlphaGo artificial intelligence, be­cause “Even if I become the No. 1, there is an entity that cannot be defeated”. It is our great luck that we do not need to compete or defeat it, we must ensure instead that it would be safe and trustworthy, and in collaboration with humans this entity would make healthcare more effective and efficient. ]

Acquired idiopathic generalised anhidrosis is an uncommon sweating disorder characterized by loss of sweating in the absence of any neurologic, metabolic or sweat gland abnormalities. Although some possible immunological and structural mechanisms have been proposed for this rare entity, the definitive pathophysiology is still un­clear. Despite some successfully treated cases with systemic corticosteroid application, the dose and route of steroid application are controversial. Here, we present a 41-year-old man with lack of genera­lised sweating who has been successfully treated with high dose pulse intravenous prednisolone. We have discussed his clinical and histopathological findings as well as the treatment options in view of the current literature.

The syndrome of headache with neurologic deficits and cerebrospinal fluid lymphocytosis (HaNDL) is a rare entity. This disease has been related to migrainous headaches. It is a benign, self-limited disorder, which is characterized by fluctuating neurological symptoms and cerebrospinal fluid lymphocytosis. We describe a case of a 47 years old man with acute onset of headache and aphasia. Cerebrospinal fluid analysis revealed a lymphocytic pleocytosis (25 cells/μl, 100% lymphocytes). Electroencephalogram showed moderate slow rhythm in the left hemisphere, with temporoparietal predominance, and without epileptiform activity. His blood tests as well as magnetic resonance imaging (MRI) results were normal. With the diagnosis of HaNDL syndrome the patient was accepted in the Department of Neurology and discharged with full recovery.