873 resultados para Primary somatosensory cortex
Resumo:
Among other auditory operations, the analysis of different sound levels received at both ears is fundamental for the localization of a sound source. These so-called interaural level differences, in animals, are coded by excitatory-inhibitory neurons yielding asymmetric hemispheric activity patterns with acoustic stimuli having maximal interaural level differences. In human auditory cortex, the temporal blood oxygen level-dependent (BOLD) response to auditory inputs, as measured by functional magnetic resonance imaging (fMRI), consists of at least two independent components: an initial transient and a subsequent sustained signal, which, on a different time scale, are consistent with electrophysiological human and animal response patterns. However, their specific functional role remains unclear. Animal studies suggest these temporal components being based on different neural networks and having specific roles in representing the external acoustic environment. Here we hypothesized that the transient and sustained response constituents are differentially involved in coding interaural level differences and therefore play different roles in spatial information processing. Healthy subjects underwent monaural and binaural acoustic stimulation and BOLD responses were measured using high signal-to-noise-ratio fMRI. In the anatomically segmented Heschl's gyrus the transient response was bilaterally balanced, independent of the side of stimulation, while in opposite the sustained response was contralateralized. This dissociation suggests a differential role at these two independent temporal response components, with an initial bilateral transient signal subserving rapid sound detection and a subsequent lateralized sustained signal subserving detailed sound characterization.
Resumo:
Excitatory neurons at the level of cortical layer 4 in the rodent somatosensory barrel field often display a strong eccentricity in comparison with layer 4 neurons in other cortical regions. In rat, dendritic symmetry of the 2 main excitatory neuronal classes, spiny stellate and star pyramid neurons (SSNs and SPNs), was quantified by an asymmetry index, the dendrite-free angle. We carefully measured shrinkage and analyzed its influence on morphological parameters. SSNs had mostly eccentric morphology, whereas SPNs were nearly radially symmetric. Most asymmetric neurons were located near the barrel border. The axonal projections, analyzed at the level of layer 4, were mostly restricted to a single barrel except for those of 3 interbarrel projection neurons. Comparing voxel representations of dendrites and axon collaterals of the same neuron revealed a close overlap of dendritic and axonal fields, more pronounced in SSNs versus SPNs and considerably stronger in spiny L4 neurons versus extragranular pyramidal cells. These observations suggest that within a barrel dendrites and axons of individual excitatory cells are organized in subcolumns that may confer receptive field properties such as directional selectivity to higher layers, whereas the interbarrel projections challenge our view of barrels as completely independent processors of thalamic input.
Resumo:
Larger body parts are somatotopically represented in the primary motor cortex (M1), while smaller body parts, such as the fingers, have partially overlapping representations. The principles that govern the overlapping organization of M1 remain unclear. We used transcranial magnetic stimulation (TMS) to examine the cortical encoding of thumb movements in M1 of healthy humans. We performed M1 mapping of the probability of inducing a thumb movement in a particular direction and used low intensity TMS to disturb a voluntary thumb movement in the same direction during a reaction time task. With both techniques we found spatially segregated representations of the direction of TMS-induced thumb movements, thumb flexion and extension being best separated. Furthermore, the cortical regions corresponding to activation of a thumb muscle differ, depending on whether the muscle functions as agonist or as antagonist for flexion or extension. In addition, we found in the reaction time experiment that the direction of a movement is processed in M1 before the muscles participating in it are activated. It thus appears that one of the organizing principles for the human corticospinal motor system is based on a spatially segregated representation of movement directions and that the representation of individual somatic structures, such as the hand muscles, overlap.
Resumo:
Inappropriate response tendencies may be stopped via a specific fronto/basal ganglia/primary motor cortical network. We sought to characterize the functional role of two regions in this putative stopping network, the right inferior frontal gyrus (IFG) and the primary motor cortex (M1), using electocorticography from subdural electrodes in four patients while they performed a stop-signal task. On each trial, a motor response was initiated, and on a minority of trials a stop signal instructed the patient to try to stop the response. For each patient, there was a greater right IFG response in the beta frequency band ( approximately 16 Hz) for successful versus unsuccessful stop trials. This finding adds to evidence for a functional network for stopping because changes in beta frequency activity have also been observed in the basal ganglia in association with behavioral stopping. In addition, the right IFG response occurred 100-250 ms after the stop signal, a time range consistent with a putative inhibitory control process rather than with stop-signal processing or feedback regarding success. A downstream target of inhibitory control is M1. In each patient, there was alpha/beta band desynchronization in M1 for stop trials. However, the degree of desynchronization in M1 was less for successfully than unsuccessfully stopped trials. This reduced desynchronization on successful stop trials could relate to increased GABA inhibition in M1. Together with other findings, the results suggest that behavioral stopping is implemented via synchronized activity in the beta frequency band in a right IFG/basal ganglia network, with downstream effects on M1.
Resumo:
More than a century ago Ramon y Cajal pioneered the description of neural circuits. Currently, new techniques are being developed to streamline the characterization of entire neural circuits. Even if this 'connectome' approach is successful, it will represent only a static description of neural circuits. Thus, a fundamental question in neuroscience is to understand how information is dynamically represented by neural populations. In this thesis, I studied two main aspects of dynamical population codes. ^ First, I studied how the exposure or adaptation, for a fraction of a second to oriented gratings dynamically changes the population response of primary visual cortex neurons. The effects of adaptation to oriented gratings have been extensively explored in psychophysical and electrophysiological experiments. However, whether rapid adaptation might induce a change in the primary visual cortex's functional connectivity to dynamically impact the population coding accuracy is currently unknown. To address this issue, we performed multi-electrode recordings in primary visual cortex, where adaptation has been previously shown to induce changes in the selectivity and response amplitude of individual neurons. We found that adaptation improves the population coding accuracy. The improvement was more prominent for iso- and orthogonal orientation adaptation, consistent with previously reported psychophysical experiments. We propose that selective decorrelation is a metabolically inexpensive mechanism that the visual system employs to dynamically adapt the neural responses to the statistics of the input stimuli to improve coding efficiency. ^ Second, I investigated how ongoing activity modulates orientation coding in single neurons, neural populations and behavior. Cortical networks are never silent even in the absence of external stimulation. The ongoing activity can account for up to 80% of the metabolic energy consumed by the brain. Thus, a fundamental question is to understand the functional role of ongoing activity and its impact on neural computations. I studied how the orientation coding by individual neurons and cell populations in primary visual cortex depend on the spontaneous activity before stimulus presentation. We hypothesized that since the ongoing activity of nearby neurons is strongly correlated, it would influence the ability of the entire population of orientation-selective cells to process orientation depending on the prestimulus spontaneous state. Our findings demonstrate that ongoing activity dynamically filters incoming stimuli to shape the accuracy of orientation coding by individual neurons and cell populations and this interaction affects behavioral performance. In summary, this thesis is a contribution to the study of how dynamic internal states such as rapid adaptation and ongoing activity modulate the population code accuracy. ^
Resumo:
Primary motor cortex (M1) is involved in the production of voluntary movement and contains a complete functional representation, or map, of the skeletal musculature. This functional map can be altered by pathological experiences, such as peripheral nerve injury or stroke, by pharmacological manipulation, and by behavioral experience. The process by which experience-dependent alterations of cortical function occur is termed plasticity. In this thesis, plasticity of M1 functional organization as a consequence of behavioral experience was examined in adult primates (squirrel monkeys). Maps of movement representations were derived under anesthesia using intracortical microstimulation, whereby a microelectrode was inserted into the cortex to electrically stimulate corticospinal neurons at low current levels and evoke movements of the forelimb, principally of the hand. Movement representations were examined before and at several times after training on behavioral tasks that emphasized use of the fingers. Two behavioral tasks were utilized that dissociated the repetition of motor activity from the acquisition of motor skills. One task was easy to perform, and as such promoted repetitive motor activity without learning. The other task was more difficult, requiring the acquisition of motor skills for successful performance. Kinematic analysis indicated that monkeys used a consistent set of forelimb movements during pellet extractions. Functional mapping revealed that repetitive motor activity during the easier task did not produce plastic changes in movement representations. Instead, map plasticity, in the form of selective expansions of task-related movement representations, was only produced following skill acquisition on the difficult task. Additional studies revealed that, in general, map plasticity persisted without further training for up to three months, in parallel with the retention of task-related motor skills. Also, extensive additional training on the small well task produced further improvements in performance, and further changes in movement maps. In sum, these experiments support the following three conclusions regarding the role of M1 in motor learning. First, behaviorally-driven plasticity is learning-dependent, not activity-dependent. Second, plastic changes in M1 functional representations represent a neural correlate of acquired motor skills. Third, the persistence of map plasticity suggests that M1 is part of the neural substrate for the memory of motor skills. ^
Resumo:
Within the regression framework, we show how different levels of nonlinearity influence the instantaneous firing rate prediction of single neurons. Nonlinearity can be achieved in several ways. In particular, we can enrich the predictor set with basis expansions of the input variables (enlarging the number of inputs) or train a simple but different model for each area of the data domain. Spline-based models are popular within the first category. Kernel smoothing methods fall into the second category. Whereas the first choice is useful for globally characterizing complex functions, the second is very handy for temporal data and is able to include inner-state subject variations. Also, interactions among stimuli are considered. We compare state-of-the-art firing rate prediction methods with some more sophisticated spline-based nonlinear methods: multivariate adaptive regression splines and sparse additive models. We also study the impact of kernel smoothing. Finally, we explore the combination of various local models in an incremental learning procedure. Our goal is to demonstrate that appropriate nonlinearity treatment can greatly improve the results. We test our hypothesis on both synthetic data and real neuronal recordings in cat primary visual cortex, giving a plausible explanation of the results from a biological perspective.
Resumo:
The occurrence of cortical plasticity during adulthood has been demonstrated using many experimental paradigms. Whether this phenomenon is generated exclusively by changes in intrinsic cortical circuitry, or whether it involves concomitant cortical and subcortical reorganization, remains controversial. Here, we addressed this issue by simultaneously recording the extracellular activity of up to 135 neurons in the primary somatosensory cortex, ventral posterior medial nucleus of the thalamus, and trigeminal brainstem complex of adult rats, before and after a reversible sensory deactivation was produced by subcutaneous injections of lidocaine. Following the onset of the deactivation, immediate and simultaneous sensory reorganization was observed at all levels of the somatosensory system. No statistical difference was observed when the overall spatial extent of the cortical (9.1 ± 1.2 whiskers, mean ± SE) and the thalamic (6.1 ± 1.6 whiskers) reorganization was compared. Likewise, no significant difference was found in the percentage of cortical (71.1 ± 5.2%) and thalamic (66.4 ± 10.7%) neurons exhibiting unmasked sensory responses. Although unmasked cortical responses occurred at significantly higher latencies (19.6 ± 0.3 ms, mean ± SE) than thalamic responses (13.1 ± 0.6 ms), variations in neuronal latency induced by the sensory deafferentation occurred as often in the thalamus as in the cortex. These data clearly demonstrate that peripheral sensory deafferentation triggers a system-wide reorganization, and strongly suggest that the spatiotemporal attributes of cortical plasticity are paralleled by subcortical reorganization.
Resumo:
The monkey premotor cortex contains neurons that discharge during action execution and during observation of actions made by others. Transcranial magnetic stimulation experiments suggest that a similar observation/execution matching system also is present in humans. We recorded neuromagnetic oscillatory activity of the human precentral cortex from 10 healthy volunteers while (i) they had no task to perform, (ii) they were manipulating a small object, and (iii) they were observing another individual performing the same task. The left and right median nerves were stimulated alternately (interstimulus interval, 1.5 s) at intensities exceeding motor threshold, and the poststimulus rebound of the rolandic 15- to 25-Hz activity was quantified. In agreement with previous studies, the rebound was strongly suppressed bilaterally during object manipulation. Most interestingly, the rebound also was significantly diminished during action observation (31–46% of the suppression during object manipulation). Control experiments, in which subjects were instructed to observe stationary or moving stimuli, confirmed the specificity of the suppression effect. Because the recorded 15- to 25-Hz activity is known to originate mainly in the precentral motor cortex, we concluded that the human primary motor cortex is activated during observation as well as execution of motor tasks. These findings have implications for a better understanding of the machinery underlying action recognition in humans.
Resumo:
We optically imaged a visual masking illusion in primary visual cortex (area V-1) of rhesus monkeys to ask whether activity in the early visual system more closely reflects the physical stimulus or the generated percept. Visual illusions can be a powerful way to address this question because they have the benefit of dissociating the stimulus from perception. We used an illusion in which a flickering target (a bar oriented in visual space) is rendered invisible by two counter-phase flickering bars, called masks, which flank and abut the target. The target and masks, when shown separately, each generated correlated activity on the surface of the cortex. During the illusory condition, however, optical signals generated in the cortex by the target disappeared although the image of the masks persisted. The optical image thus was correlated with perception but not with the physical stimulus.
Resumo:
Proper understanding of processes underlying visual perception requires information on the activation order of distinct brain areas. We measured dynamics of cortical signals with magnetoencephalography while human subjects viewed stimuli at four visual quadrants. The signals were analyzed with minimum current estimates at the individual and group level. Activation emerged 55–70 ms after stimulus onset both in the primary posterior visual areas and in the anteromedial part of the cuneus. Other cortical areas were active after this initial dual activation. Comparison of data between species suggests that the anteromedial cuneus either comprises a homologue of the monkey area V6 or is an area unique to humans. Our results show that visual stimuli activate two cortical areas right from the beginning of the cortical response. The anteromedial cuneus has the temporal position needed to interact with the primary visual cortex V1 and thereby to modify information transferred via V1 to extrastriate cortices.
Resumo:
Human area V1 offers an excellent opportunity to study, using functional MRI, a range of properties in a specific cortical visual area, whose borders are defined objectively and convergently by retinotopic criteria. The retinotopy in V1 (also known as primary visual cortex, striate cortex, or Brodmann’s area 17) was defined in each subject by using both stationary and phase-encoded polar coordinate stimuli. Data from V1 and neighboring retinotopic areas were displayed on flattened cortical maps. In additional tests we revealed the paired cortical representations of the monocular “blind spot.” We also activated area V1 preferentially (relative to other extrastriate areas) by presenting radial gratings alternating between 6% and 100% contrast. Finally, we showed evidence for orientation selectivity in V1 by measuring transient functional MRI increases produced at the change in response to gratings of differing orientations. By systematically varying the orientations presented, we were able to measure the bandwidth of the orientation “transients” (45°).
Resumo:
Behavioral and neurophysiological studies suggest that skill learning can be mediated by discrete, experience-driven changes within specific neural representations subserving the performance of the trained task. We have shown that a few minutes of daily practice on a sequential finger opposition task induced large, incremental performance gains over a few weeks of training. These gains did not generalize to the contralateral hand nor to a matched sequence of identical component movements, suggesting that a lateralized representation of the learned sequence of movements evolved through practice. This interpretation was supported by functional MRI data showing that a more extensive representation of the trained sequence emerged in primary motor cortex after 3 weeks of training. The imaging data, however, also indicated important changes occurring in primary motor cortex during the initial scanning sessions, which we proposed may reflect the setting up of a task-specific motor processing routine. Here we provide behavioral and functional MRI data on experience-dependent changes induced by a limited amount of repetitions within the first imaging session. We show that this limited training experience can be sufficient to trigger performance gains that require time to become evident. We propose that skilled motor performance is acquired in several stages: “fast” learning, an initial, within-session improvement phase, followed by a period of consolidation of several hours duration, and then “slow” learning, consisting of delayed, incremental gains in performance emerging after continued practice. This time course may reflect basic mechanisms of neuronal plasticity in the adult brain that subserve the acquisition and retention of many different skills.