Progress in brain research
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The discovery of event-related desynchronization (ERD) and event-related synchronization (ERS) by Pfurtscheller paved the way for the development of brain-computer interfaces (BCIs). BCIs allow control of computers or external devices with the regulation of brain activity only. Two different research traditions produced two different types of BCIs: invasive BCIs, realized with implanted electrodes in brain tissue and noninvasive BCIs using electrophysiological recordings in humans such as electroencephalography (EEG) and magnetoencephalography (MEG) and metabolic changes such as functional magnetic resonance imaging (fMRI) and near infrared spectroscopy (NIRS). ⋯ Invasive multielectrode BCIs in otherwise healthy animals allowed execution of reaching, grasping, and force variations from spike patterns and extracellular field potentials. Whether invasive approaches allow superior brain control of motor responses compared to noninvasive BCI with intelligent peripheral devices and electrical muscle stimulation and EMG feedback remains to be demonstrated. The newly developed fMRI-BCIs and NIRS-BCIs offer promise for the learned regulation of emotional disorders and also disorders of small children (in the case of NIRS).
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Review
Functional genomics and proteomics in the clinical neurosciences: data mining and bioinformatics.
The goal of this chapter is to introduce some of the available computational methods for expression analysis. Genomic and proteomic experimental techniques are briefly discussed to help the reader understand these methods and results better in context with the biological significance. Furthermore, a case study is presented that will illustrate the use of these analytical methods to extract significant biomarkers from high-throughput microarray data. ⋯ The validation process may be slow; yet, the overall biomarker discovery process is significantly accelerated due to initial feature ranking and data reduction steps. Information obtained from the validation process may also be used to refine data analysis procedures for future iteration. Biomarker validation may be performed in a number of ways - bench-side in traditional labs, web-based electronic resources such as gene ontology and literature databases, and clinical trials.
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A central question in visual neuroscience is what circuits generate the responses of neurons in the primary visual cortex (V1). V1 neurons respond best to oriented stimuli of optimal size within their receptive field (RF) center. This size tuning is contrast dependent, i.e. a neuron's optimal stimulus size measured at high contrast (the high-contrast summation RF, or hsRF) is smaller than when measured using low-contrast stimuli (the low-contrast summation RF, or lsRF). ⋯ We review data showing that a subset of FB connections terminate in a patchy fashion in V1, and show modular and orientation specificity, consistent with their proposed role in orientation-specific center-surround interactions. We propose specific mechanisms by which each connection type contributes to the RF center and surround of V1 neurons, and implement these hypotheses into a recurrent network model. We show physiological data in support of the model's predictions, revealing that modulation from the "far" surround is not always suppressive, but can be facilitatory under specific stimulus conditions.
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The autonomic nervous system modulates cardiac electrophysiology and abnormalities of autonomic function are known to increase the risk of ventricular arrhythmias. The abnormal and unstable autonomic control of the cardiovascular system following spinal cord injury also is well known. ⋯ Therefore, spinal cord injury may alter cardiac electrophysiology and increase the risk for ventricular arrhythmias. In this chapter, we discuss how the autonomic changes associated with cord injury can influence cardiac electrophysiology and the susceptibility to ventricular arrhythmias.
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Review
Neural mechanisms of prefrontal cortical function: implications for cognitive rehabilitation.
Understanding the role of the frontal lobes in cognition remains a challenge for neurologists and neuroscientists. It is proposed that goal-directed behavior, at the core of what we consider human, depends critically on the function of the frontal lobes, and, specifically, the prefrontal cortex (PFC). In this chapter, we put forth the hypothesis that further insight into the neural mechanisms underlying normal PFC function may ultimately help us understand the frontal-lobe syndrome, and importantly, potentially lead to effective therapeutic interventions for frontal-lobe dysfunction. Thus, the aim of this chapter is to review current hypotheses and knowledge about the neural mechanisms underlying the normal function of the PFC in cognition that could guide the development of therapeutic interventions.