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Underlying Neural Mechanisms (underlying + neural_mechanism)
Selected AbstractsSing the mind electric , principles of deep brain stimulationEUROPEAN JOURNAL OF NEUROSCIENCE, Issue 7 2010Morten L. Kringelbach Abstract The remarkable efficacy of deep brain stimulation (DBS) for a range of treatment-resistant disorders is still not matched by a comparable understanding of the underlying neural mechanisms. Some progress has been made using translational research with a range of neuroscientific techniques, and here we review the most promising emerging principles. On balance, DBS appears to work by restoring normal oscillatory activity between a network of key brain regions. Further research using this causal neuromodulatory tool may provide vital insights into fundamental brain function, as well as guide targets for future treatments. In particular, DBS could have an important role in restoring the balance of the brain's default network and thus repairing the malignant brain states associated with affective disorders, which give rise to serious disabling problems such as anhedonia, the lack of pleasure. At the same time, it is important to proceed with caution and not repeat the errors from the era of psychosurgery. [source] Dissociation of food and opiate preference by a genetic mutation in zebrafishGENES, BRAIN AND BEHAVIOR, Issue 7 2006B. Lau Both natural rewards and addictive substances have the ability to reinforce behaviors. It has been unclear whether identical neural pathways mediate the actions of both. In addition, little is known about these behaviors and the underlying neural mechanisms in a genetically tractable vertebrate, the zebrafish Danio rerio. Using a conditioned place preference paradigm, we demonstrate that wildtype zebrafish exhibit a robust preference for food as well as the opiate drug morphine that can be blocked by the opioid receptor antagonist naloxone. Moreover, we show that the too few mutant, which disrupts a conserved zinc finger-containing gene and exhibits a reduction of selective groups of dopaminergic and serotonergic neurons in the basal diencephalon, displays normal food preference but shows no preference for morphine. Pretreatment with dopamine receptor antagonists abolishes morphine preference in the wildtype. These studies demonstrate that zebrafish display measurable preference behavior for reward and show that the preference for natural reward and addictive drug is dissociable by a single-gene mutation that alters subregions of brain monoamine neurotransmitter systems. Future genetic analysis in zebrafish shall uncover further molecular and cellular mechanisms underlying the formation and function of neural circuitry that regulate opiate and food preference behavior. [source] Enhanced effectiveness in visuo-haptic object-selective brain regions with increasing stimulus salienceHUMAN BRAIN MAPPING, Issue 5 2010Sunah Kim Abstract The occipital and parietal lobes contain regions that are recruited for both visual and haptic object processing. The purpose of the present study was to characterize the underlying neural mechanisms for bimodal integration of vision and haptics in these visuo-haptic object-selective brain regions to find out whether these brain regions are sites of neuronal or areal convergence. Our sensory conditions consisted of visual-only (V), haptic-only (H), and visuo-haptic (VH), which allowed us to evaluate integration using the superadditivity metric. We also presented each stimulus condition at two different levels of signal-to-noise ratio or salience. The salience manipulation allowed us to assess integration using the rule of inverse effectiveness. We were able to localize previously described visuo-haptic object-selective regions in the lateral occipital cortex (lateral occipital tactile-visual area) and the intraparietal sulcus, and also localized a new region in the left anterior fusiform gyrus. There was no evidence of superadditivity with the VH stimulus at either level of salience in any of the regions. There was, however, a strong effect of salience on multisensory enhancement: the response to the VH stimulus was more enhanced at higher salience across all regions. In other words, the regions showed enhanced integration of the VH stimulus with increasing effectiveness of the unisensory stimuli. We called the effect "enhanced effectiveness." The presence of enhanced effectiveness in visuo-haptic object-selective brain regions demonstrates neuronal convergence of visual and haptic sensory inputs for the purpose of processing object shape. Hum Brain Mapp, 2010. © 2009 Wiley-Liss, Inc. [source] Changes in neural activity associated with learning to articulate novel auditory pseudowords by covert repetitionHUMAN BRAIN MAPPING, Issue 11 2008Andreas M. Rauschecker Abstract Learning to articulate novel combinations of phonemes that form new words through a small number of auditory exposures is crucial for development of language and our capacity for fluent speech, yet the underlying neural mechanisms are largely unknown. We used functional magnetic resonance imaging to reveal repetition,suppression effects accompanying such learning and reflecting discrete changes in brain activity due to stimulus-specific fine-tuning of neural representations. In an event-related design, subjects were repeatedly exposed to auditory pseudowords, which they covertly repeated. Covert responses during scanning and postscanning overt responses showed evidence of learning. An extensive set of regions activated bilaterally when listening to and covertly repeating novel pseudoword stimuli. Activity decreased, with repeated exposures, in a subset of these areas mostly in the left hemisphere, including premotor cortex, supplementary motor area, inferior frontal gyrus, superior temporal cortex, and cerebellum. The changes most likely reflect more efficient representation of the articulation patterns of these novel words in two connected systems, one involved in the perception of pseudoword stimuli (in the left superior temporal cortex) and one for processing the output of speech (in the left frontal cortex). Both of these systems contribute to vocal learning. Hum Brain Mapp 2008. © 2007 Wiley-Liss, Inc. [source] | ||||||||||