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Korbinian Brodmann (1868–1918)
Published in Andrew P. Wickens, Key Thinkers in Neuroscience, 2018
Again, as might be expected, the chapters illustrating the human cerebral cortex generated the most interest. Although his map of the human cortex on first sight displays forty-seven different cytoarchitectonic areas, with the numbers simply indicating the order in which he studied them, a close scrutiny of his diagrams actually shows that certain numbers (areas 12–16) are missing. Brodmann accounted for these “gaps” by explaining that some regions such as the olfactory, limbic and insular cortices are not identifiable in the human cortex but well developed in other mammalian species. To complicate matters, four other regions (numbers 48–52) are not shown in the human cortical map, although they appear elsewhere in the text. Nonetheless, it was apparent that the human cerebral cortex is significantly more complex than that found in monkeys and the great apes, which only have around thirty areas.
Maps of the Visual Field in the Cerebral Cortex of Primates: Functional Organization and Significance
Published in Jon H. Kaas, Christine E. Collins, The Primate Visual System, 2003
Marcello G. P. Rosa, Rowan Tweedale
In contrast, second-order representations are those in which the topological equivalence between the visual field and the cortex is violated in some way. One clear illustration of a second-order map is found in V2 (Figure 11.3B). In this area, the upper and lower quadrants of the contralateral hemifield are represented in separate locations (in ventral and dorsal occipital cortex, respectively), connected only by a small bridge where the fovea is represented.11,42,44 Thus, despite the representations of the upper and lower contralateral quadrants in V2 as internally continuous (e.g., points a and b, or c and d), the representations of points above or below the horizontal meridian of the visual field become nonadjacent in the cortical map (e.g., points b and c).
Cortical Plasticity: Growth of New Connections Can Contribute to Reorganization
Published in Mark J Rowe, Yoshiaki Iwamura, Somatosensory Processing: From Single Neuron to Brain Imaging, 2001
Sherre L. Florence, Jon H. Kaas
Because the density of the expanded inputs observed in the cuneate nucleus after amputation was sparse, we reasoned that the impact of the reorganization at this level would have the most effect on higher-order processing stations if potentiated by additional changes that occur at thalamic and cortical levels. These higher-level changes could be limited to the sorts of local alterations that appear to mediate the use-dependent changes in sensory representations. However, we did not rule out the possibility that sprouting also could occur at other levels of the pathway after such a profound injury. Thus, in a second series of monkeys, we have studied the patterns of corticocortical and thalamocortical connections that had either amputation or injury to the hand. To test whether the changes in cortical topography after forelimb injury were accompanied by structural changes in the deprived sensory representation, we injected minute volumes of neuroanatomical tracers into a part of the reorganized cortical map (i.e. into the zone that would likely have contained the hand representation). In normal monkeys, such an injection labels a zone in cortex that is roughly topographically matched to the region injected; for example, if the representation of D1 in area 1 is injected, the projection is concentrated in the D1 representation in area 3b and extends only a millimeter or so into neighboring representations (Fig. 11.5; Florence et al., 1998). The total mediolateral extent of label produced by a mm diameter injection in normal monkeys ranges from 3-4 mm. However, in the three monkeys with longstanding injuries to the hand, the distribution of cortical label was much more widely distributed (Fig. 11.5). For example, in a monkey that had amputation of the fingers on one hand, an injection that was matched in size to those in the normal monkeys produced a labeled zone that spanned 6.2 mm in total mediolateral extent. In a monkey that had a paralyzed hand, the span of label was even larger (more than 7 mm), and in a monkey with a complete arm amputation, the labeled zone was larger still, extending 8.9 mm mediolaterally (Fig. 11.7). This indicates that, as a result of the injury, cortical neurons had sprouted new axon processes over relatively long distances into and out of the deprived region of cortex.
Transcranial direct current stimulation (tDCS) paired with massed practice training to promote adaptive plasticity and motor recovery in chronic incomplete tetraplegia: A pilot study
Published in The Journal of Spinal Cord Medicine, 2018
Kelsey A. Potter-Baker, Daniel P. Janini, Yin-Liang Lin, Vishwanath Sankarasubramanian, David A. Cunningham, Nicole M. Varnerin, Patrick Chabra, Kevin L. Kilgore, Mary Ann Richmond, Frederick S. Frost, Ela B. Plow
We also evaluated the motor map distribution by determining the number of map sites at which the MEP amplitude exceeded 25%, 50% and 75% of the maximum MEP (M-MEP) elicited in the map for each muscle (Fig. 5B). The goal of this additional analysis was to determine whether the cortical map representations were more focused or diffuse following intervention. In general, we found that the distribution of MEP amplitudes did not substantially change in the strong muscle at post-test (data not shown). In contrast, we did note a change in MEP distribution in the weak muscle representation at post-test between groups. In the tDCS+MP group, we observed that the weak muscle motor map had become more focused. As displayed in Fig. 5B, the average percentage of map sites that demonstrated MEPs >75% the maximum MEP (M-MEP) changed from 17% to 29% between pre-test #2 and post-test for the tDCS+MP group. Taken together, this indicated that although less motor map sites were actively eliciting MEPs in the tDCS+MP group, sites that were excitable were more robust and focalized. Notice also that participants demonstrating such a more focused weak map muscle representation at post-test were also those with the most improvements in UEMS at post-test (r=0.675).
Paradoxes in rehabilitation
Published in Disability and Rehabilitation, 2020
One common illusion to which we are all prone is the idea that, when our foot hurts, the pain we experience is in our foot rather than in our brain. This illusion is no more dramatically revealed than when, following limb amputation, people experience crippling pain in the now absent limb. This “phantom limb pain” is disturbing, not least because normal strategies such as rubbing or flexing the hurt area are not available. A novel approach to helping such patients has been to create the illusion that the absent limb is still present. This is achieved using a mirror to reflect the remaining limb in the location of the missing limb, often using a mirror box, hence the term Mirror Box Illusion. Remarkably, despite the patients knowing that they are not seeing their absent limb, over a large number of trials the illusion of cramp relieving movement can reduce the pain, sometimes permanently [40–41]. A randomized control trial [42] found that mirror therapy was effective in reducing the intensity, duration and frequency of phantom limb pain. Presumably, the “latent” cortical map of the missing limb somehow gets activated. In some amputees, however, phantom limb movement can actually result in an increase in phantom limb pain, and a variation of the Mirror Box Illusion has been developed, whereby patients look at the mirror reflection of touches applied to the intact hand, while at the same time receiving touches on the remnant stump which is positioned behind the mirror. The illusion that is generated – of touch sensations on the phantom hand – has been found to reduce phantom limb pain in patients who do not respond to the standard mirror box illusion [43]. It may therefore be the case that different forms of the illusion will help different patients.
The simultaneous changes in motor performance and EEG patterns in beta band during learning dart throwing skill in dominant and non-dominant hand
Published in Computer Methods in Biomechanics and Biomedical Engineering, 2023
Yaser Khanjari, Elahe Arabameri, Mehdi Shahbazi, Shahzad Tahmasebi, Fariba Bahrami, Ali Mobaien
In the present study, due to the similarity of EEG activity patterns in the acquisition and retention stages, it seems that the cortical results obtained are related to the concept of motor learning. According to the definition of motor learning, which is a relatively constant change in motor performance that is related to practice and experience (Wolpert et al. 2001), the results of this study also show that with continued training and skill development, these relatively constant changes can also be deduced in level the brain. Previous research has shown that the quality of the learned movement remains the same even in the absence of exercise, and it is believed that motor skills are coded and stored during neuro-physiological changes in areas of the motor cortex of the central nervous system (Ito 2002). Other studies in rats have shown that if exercise such as access accuracy is eliminated in the early stages, changes in cortical map do not occur, even if access accuracy is significantly improved. These results show that the reorganization of the cortical map can indicate the consolidation of motor skills so that in the absence of training, motor skills are still preserved without destruction (Monfils et al. 2005). Therefore, considering that in this study, a retention test was performed after one week of training and the results of EEG activity patterns and dart throw performance in acquisition and retention are very similar with each other, the concept of motor learning can be inferred at the brain level, which may be referred to as brain activity learning. Yoshimura et al. (2017) in their study of decoding finger movements using cortical flow signals showed that the simultaneous activity of neuronal masses present in different areas of the brain probably reflects the coordinated interactions of neural networks in different areas of the brain that can reflect the formation of the motor program and execution (Yoshimura et al. 2017). In this study, the relatively stable changes of the brain mapping pattern in the frontal, central, and parietal-occipital areas after a week without exercise could possibly be a reflection of learning the skill motor program.