Complex spatio-temporal dynamics of fMRI BOLD: A study of motor learning

Detection of Activation Sequences in Spiking-Bursting Neurons by means of the Recognition of Intraburst Neural Signatures

Bursting activity is present in many cells of different nervous systems playing important roles in neural information processing. Multiple assemblies of bursting neurons act cooperatively to produce coordinated spatio-temporal patterns of sequential activity. A major goal in neuroscience is unveiling the mechanisms underlying neural information processing based on this sequential dynamics. Experimental findings have revealed the presence of precise cell-type-specific intraburst firing patterns in the activity of some bursting neurons. This characteristic neural signature coexists with the information encoded in other aspects of the spiking-bursting signals, and its functional meaning is still unknown. We investigate the ability of a neuron conductance-based model to detect specific presynaptic activation sequences taking advantage of intraburst fingerprints identifying the source of the signals building up a sequential pattern of activity. Our simulations point out that a reader neuron could use this information to contextualize incoming signals and accordingly compute a characteristic response by relying on precise phase relationships among the activity of different emitters. This would provide individual neurons enhanced capabilities to control and negotiate sequential dynamics. In this regard, we discuss the possible implications of the proposed contextualization mechanism for neural information processing.

The activity in the contralateral primary motor cortex, dorsal premotor and supplementary motor area is modulated by performance gains

There is growing experimental evidence that the engagement of different brain areas in a given motor task may change with practice, although the specific brain activity patterns underlying different stages of learning, as defined by kinematic or dynamic performance indices, are not well understood. Here we studied the change in activation in motor areas during practice on sequences of handwriting-like trajectories, connecting four target points on a digitizing table “as rapidly and as accurately as possible” while lying inside an fMRI scanner. Analysis of the subjects' pooled kinematic and imaging data, acquired at the beginning, middle, and end of the training period, revealed no correlation between the amount of activation in the contralateral M1, PM (dorsal and ventral), supplementary motor area (SMA), preSMA, and Posterior Parietal Cortex (PPC) and the amount of practice per-se. Single trial analysis has revealed that the correlation between the amount of activation in the contralateral M1 and trial mean velocity was partially modulated by performance gains related effects, such as increased hand motion smoothness. Furthermore, it was found that the amount of activation in the contralateral preSMA increased when subjects shifted from generating straight point-to-point trajectories to their spatiotemporal concatenation into a smooth, curved trajectory. Altogether, our results indicate that the amount of activation in the contralateral M1, PMd, and preSMA during the learning of movement sequences is correlated with performance gains and that high level motion features (e.g., motion smoothness) may modulate, or even mask correlations between activity changes and low-level motion attributes (e.g., trial mean velocity).

If it bleeds, it leads: separating threat from mere negativity

Most theories of emotion hold that negative stimuli are threatening and aversive. Yet in everyday experiences some negative sights (e.g. car wrecks) attract curiosity, whereas others repel (e.g. a weapon pointed in our face). To examine the diversity in negative stimuli, we employed four classes of visual images (Direct Threat, Indirect Threat, Merely Negative and Neutral) in a set of behavioral and functional magnetic resonance imaging studies. Participants reliably discriminated between the images, evaluating Direct Threat stimuli most quickly, and Merely Negative images most slowly. Threat images evoked greater and earlier blood oxygen level-dependent (BOLD) activations in the amygdala and periaqueductal gray, structures implicated in representing and responding to the motivational salience of stimuli. Conversely, the Merely Negative images evoked larger BOLD signal in the parahippocampal, retrosplenial, and medial prefrontal cortices, regions which have been implicated in contextual association processing. Ventrolateral as well as medial and lateral orbitofrontal cortices were activated by both threatening and Merely Negative images. In conclusion, negative visual stimuli can repel or attract scrutiny depending on their current threat potential, which is assessed by dynamic shifts in large-scale brain network activity.

Spatial-temporal modelling of fMRI data through spatially regularized mixture of hidden process models

Previous work investigated a range of spatio-temporal constraints for fMRI data analysis to provide robust detection of neural activation. We present a mixture-based method for the spatio-temporal modelling of fMRI data. This approach assumes that fMRI time series are generated by a probabilistic superposition of a small set of spatio-temporal prototypes (mixture components). Each prototype comprises a temporal model that explains fMRI signals on a single voxel and the model's "region of influence" through a spatial prior over the voxel space. As the key ingredient of our temporal model, the Hidden Process Model (HPM) framework proposed in Hutchinson et al. (2009) is adopted to infer the overlapping cognitive processes triggered by stimuli. Unlike the original HPM framework, we use a parametric model of Haemodynamic Response Function (HRF) so that biological constraints are naturally incorporated in the HRF estimation. The spatial priors are defined in terms of a parameterised distribution. Thus, the total number of parameters in the model does not depend on the number of voxels. The resulting model provides a conceptually principled and computationally efficient approach to identify spatio-temporal patterns of neural activation from fMRI data, in contrast to most conventional approaches in the literature focusing on the detection of spatial patterns. We first verify the proposed model in a controlled experimental setting using synthetic data. The model is further validated on real fMRI data obtained from a rapid event-related visual recognition experiment (Mayhew et al., 2012). Our model enables us to evaluate in a principled manner the variability of neural activations within individual regions of interest (ROIs). The results strongly suggest that, compared with occipitotemporal regions, the frontal ones are less homogeneous, requiring two HPM prototypes per region. Despite the rapid event-related experimental design, the model is capable of disentangling the perceptual judgement and motor response processes that are both activated in the frontal ROIs. Spatio-temporal heterogeneity in the frontal regions seems to be associated with diverse dynamic localizations of the two hidden processes in different subregions of frontal ROIs.

Striatal denervation pattern predicts levodopa effects on sequence learning in Parkinson's disease

Mild to moderate Parkinson's disease shows more denervation in the posterodorsal striatum and sparing of the anteroventral striatum. Dopaminergic medications can interfere with anteroventral striatum function by overdosing this relatively intact structure. The authors determined how regional striatal denervation affects medication-associated sequence learning impairment in Parkinson's disease. Eighteen Parkinson's patients performed motor sequence learning on and off levodopa. Patients underwent (11)C-dihydrotetrabenazine positron emission tomography scans to measure nigrostriatal denervation. Patients with more preserved putamen were more likely to exhibit levodopa-associated sequence learning impairments. Furthermore, the ratio of denervation in the anterior to posterior dorsal putamen predicted the level of learning differences on and off levodopa. These results demonstrate that the spatial pattern of nigrostriatal dopaminergic denervation predicts medication responsiveness for motor sequence learning.

Poststimulus undershoots in cerebral blood flow and BOLD fMRI responses are modulated by poststimulus neuronal activity

fMRI is the foremost technique for noninvasive measurement of human brain function. However, its utility is limited by an incomplete understanding of the relationship between neuronal activity and the hemodynamic response. Though the primary peak of the hemodynamic response is modulated by neuronal activity, the origin of the typically negative poststimulus signal is poorly understood and its amplitude assumed to covary with the primary response. We use simultaneous recordings of EEG with blood oxygenation level-dependent (BOLD) and cerebral blood flow (CBF) fMRI during unilateral median nerve stimulation to show that the poststimulus fMRI signal is neuronally modulated. We observe high spatial agreement between concurrent BOLD and CBF responses to median nerve stimulation, with primary signal increases in contralateral sensorimotor cortex and primary signal decreases in ipsilateral sensorimotor cortex. During the poststimulus period, the amplitude and directionality (positive/negative) of the BOLD signal in both contralateral and ipsilateral sensorimotor cortex depends on the poststimulus synchrony of 8-13 Hz EEG neuronal activity, which is often considered to reflect cortical inhibition, along with concordant changes in CBF and metabolism. Therefore we present conclusive evidence that the fMRI time course represents a hemodynamic signature of at least two distinct temporal phases of neuronal activity, substantially improving understanding of the origin of the BOLD response and increasing the potential measurements of brain function provided by fMRI. We suggest that the poststimulus EEG and fMRI responses may be required for the resetting of the entire sensory network to enable a return to resting-state activity levels.

Neural pathways mediating cross education of motor function

Cross education is the process whereby training of one limb gives rise to enhancements in the performance of the opposite, untrained limb. Despite interest in this phenomenon having been sustained for more than a century, a comprehensive explanation of the mediating neural mechanisms remains elusive. With new evidence emerging that cross education may have therapeutic utility, the need to provide a principled evidential basis upon which to design interventions becomes ever more pressing. Generally, mechanistic accounts of cross education align with one of two explanatory frameworks. Models of the “cross activation” variety encapsulate the observation that unilateral execution of a movement task gives rise to bilateral increases in corticospinal excitability. The related conjecture is that such distributed activity, when present during unilateral practice, leads to simultaneous adaptations in neural circuits that project to the muscles of the untrained limb, thus facilitating subsequent performance of the task. Alternatively, “bilateral access” models entail that motor engrams formed during unilateral practice, may subsequently be utilized bilaterally—that is, by the neural circuitry that constitutes the control centers for movements of both limbs. At present there is a paucity of direct evidence that allows the corresponding neural processes to be delineated, or their relative contributions in different task contexts to be ascertained. In the current review we seek to synthesize and assimilate the fragmentary information that is available, including consideration of knowledge that has emerged as a result of technological advances in structural and functional brain imaging. An emphasis upon task dependency is maintained throughout, the conviction being that the neural mechanisms that mediate cross education may only be understood in this context.

Concurrent TMS to the primary motor cortex augments slow motor learning

Transcranial magnetic stimulation (TMS) has shown promise as a treatment tool, with one FDA approved use. While TMS alone is able to up- (or down-) regulate a targeted neural system, we argue that TMS applied as an adjuvant is more effective for repetitive physical, behavioral and cognitive therapies, that is, therapies which are designed to alter the network properties of neural systems through Hebbian learning. We tested this hypothesis in the context of a slow motor learning paradigm. Healthy right-handed individuals were assigned to receive 5 Hz TMS (TMS group) or sham TMS (sham group) to the right primary motor cortex (M1) as they performed daily motor practice of a digit sequence task with their non-dominant hand for 4 weeks. Resting cerebral blood flow (CBF) was measured by H2(15)O PET at baseline and after 4 weeks of practice. Sequence performance was measured daily as the number of correct sequences performed, and modeled using a hyperbolic function. Sequence performance increased significantly at 4 weeks relative to baseline in both groups. The TMS group had a significant additional improvement in performance, specifically, in the rate of skill acquisition. In both groups, an improvement in sequence timing and transfer of skills to non-trained motor domains was also found. Compared to the sham group, the TMS group demonstrated increases in resting CBF specifically in regions known to mediate skill learning namely, the M1, cingulate cortex, putamen, hippocampus, and cerebellum. These results indicate that TMS applied concomitantly augments behavioral effects of motor practice, with corresponding neural plasticity in motor sequence learning network. These findings are the first demonstration of the behavioral and neural enhancing effects of TMS on slow motor practice and have direct application in neurorehabilitation where TMS could be applied in conjunction with physical therapy.

Task-dependent interactions between dopamine D2 receptor polymorphisms and L-DOPA in patients with Parkinson's disease

Variants in genes regulating dopamine transmission affect performance on tasks including working memory and executive function as well as temporal processing and sequence learning. In the current study, we determined whether a dopamine D2 receptor DNA sequence polymorphism interacts with L-DOPA during motor tasks in patients with Parkinson's disease (PD). Forty-five PD patients were genotyped for the DRD2 polymorphism (rs 1076560, G>T). Patients performed an explicit motor sequence learning task and the grooved pegboard test in both ON and OFF L-DOPA states. For motor sequence learning, DRD2 genotype mediated L-DOPA effects such that L-DOPA associated improvements were only observed in the minor T allele carriers (associated with lower D2 receptor availability, t10=-2.71, p=0.022), whereas G homozygotes showed no performance change with L-DOPA. For the grooved pegboard test, performance improved with L-DOPA independent of patients' DRD2 genotype. Collectively these results demonstrate that common DRD2 allelic differences found in the human population may explain how dopamine differentially contributes to performance across tasks and individuals.

A quantitative meta-analysis and review of motor learning in the human brain

Neuroimaging studies have improved our understanding of which brain structures are involved in motor learning. Despite this, questions remain regarding the areas that contribute consistently across paradigms with different task demands. For instance, sensorimotor tasks focus on learning novel movement kinematics and dynamics, while serial response time task (SRTT) variants focus on sequence learning. These differing task demands are likely to elicit quantifiably different patterns of neural activity on top of a potentially consistent core network. The current study identified consistent activations across 70 motor learning experiments using activation likelihood estimation (ALE) meta-analysis. A global analysis of all tasks revealed a bilateral cortical–subcortical network consistently underlying motor learning across tasks. Converging activations were revealed in the dorsal premotor cortex, supplementary motor cortex, primary motor cortex, primary somatosensory cortex, superior parietal lobule, thalamus, putamen and cerebellum. These activations were broadly consistent across task specific analyses that separated sensorimotor tasks and SRTT variants. Contrast analysis indicated that activity in the basal ganglia and cerebellum was significantly stronger for sensorimotor tasks, while activity in cortical structures and the thalamus was significantly stronger for SRTT variants. Additional conjunction analyses then indicated that the left dorsal premotor cortex was activated across all analyses considered, even when controlling for potential motor confounds. The highly consistent activation of the left dorsal premotor cortex suggests it is a critical node in the motor learning network.

Changes in striatal dopamine release associated with human motor-skill acquisition

The acquisition of new motor skills is essential throughout daily life and involves the processes of learning new motor sequence and encoding elementary aspects of new movement. Although previous animal studies have suggested a functional importance for striatal dopamine release in the learning of new motor sequence, its role in encoding elementary aspects of new movement has not yet been investigated. To elucidate this, we investigated changes in striatal dopamine levels during initial skill-training (Day 1) compared with acquired conditions (Day 2) using ¹¹C-raclopride positron-emission tomography. Ten volunteers learned to perform brisk contractions using their non-dominant left thumbs with the aid of visual feedback. On Day 1, the mean acceleration of each session was improved through repeated training sessions until performance neared asymptotic levels, while improved motor performance was retained from the beginning on Day 2. The ¹¹C-raclopride binding potential (BP) in the right putamen was reduced during initial skill-training compared with under acquired conditions. Moreover, voxel-wise analysis revealed that ¹¹C-raclopride BP was particularly reduced in the right antero-dorsal to the lateral part of the putamen. Based on findings from previous fMRI studies that show a gradual shift of activation within the striatum during the initial processing of motor learning, striatal dopamine may play a role in the dynamic cortico-striatal activation during encoding of new motor memory in skill acquisition.

Verbal memory retrieval engages visual cortex in musicians

As one major line of research on brain plasticity, many imaging studies have been conducted to identify the functional and structural reorganization associated with musical expertise. Based on previous behavioral research, the present study used functional magnetic resonance imaging to identify the neural correlates of superior verbal memory performance in musicians. Participants with and without musical training performed a verbal memory task to first encode a list of words auditorily delivered and then silently recall as many words as possible. They performed in separate blocks a control task involving pure tone pitch judgment. Post-scan recognition test showed better memory performance in musicians than non-musicians. During memory retrieval, the musicians showed significantly greater activations in bilateral though left-lateralized visual cortex relative to the pitch judgment baseline. In comparison, no such visual cortical activations were found in the non-musicians. No group differences were observed during the encoding stage. The results echo a previous report of visual cortical activation during verbal memory retrieval in the absence of any visual sensory stimulation in the blind population, who are also known to possess superior verbal memory. It is suggested that the visual cortex can be recruited to serve as extra memory resources and contributes to the superior verbal memory in special situations. While in the blind population, such cross-modal functional reorganization may be induced by sensory deprivation; in the musicians it may be induced by the long-term and demanding nature of musical training to use as much available neural resources as possible.

The timing of emotional discrimination in human amygdala and ventral visual cortex

Models of visual emotional perception suggest a reentrant organization of the ventral visual system with the amygdala. Using focused functional magnetic resonance imaging in humans with a sampling rate of 100 ms, here we determine the relative timing of emotional discrimination in amygdala and ventral visual cortical structures during emotional perception. Results show that amygdala and inferotemporal visual cortex differentiate emotional from nonemotional scenes approximately 1 s before extrastriate occipital cortex, whereas primary occipital cortex shows consistent activity across all scenes. This pattern of discrimination is consistent with a reentrant organization of emotional perception in visual processing, in which transaction between rostral ventral visual cortex and amygdala originates the identification of emotional relevance.

Effect of dopaminergic medications on the time course of explicit motor sequence learning in Parkinson's disease

The capacity to learn new motor sequences is fundamental to adaptive motor behavior. The early phase of motor sequence learning relies on the ventral and anterior striatal circuitry, whereas the late phase relies on the dorsal and posterior striatal circuitry. Early Parkinson's disease (PD) is mainly characterized by dopaminergic denervation of the dorsal and posterior striatum while sparing anterior and ventral regions. Dopaminergic medication improves dorsal and posterior striatum function by compensating for the loss of dopamine. However, previous work has shown that dopaminergic medication interferes with the ventral and anterior striatum function by overdosing this relatively intact structure in early-state PD. Here we test whether these effects are also observed over the time course of motor sequence learning. Fourteen PD patients ON and OFF dopaminergic medications and 11 healthy age-matched control participants performed an explicit motor sequence learning task. When sequence learning was compared across different learning phases in patients ON and OFF medication, a significant impairment associated with medication was observed in the early relative to later phases of learning. The rate of learning in the early phase measured trial by trial in patients ON medication was significantly slower than that in controls and when patients were OFF medication. No significant impairment was found in the later learning phases. These results demonstrate that dopaminergic medications may selectively impair early-phase motor sequence learning. These results extend and generalize the dopamine overdose effects previously reported for (antero)ventral striatum-mediated cognitive tasks to motor sequence learning.

Long-term motor training induced changes in regional cerebral blood flow in both task and resting states

Neuroimaging studies of functional activation often only reflect differentiated involvement of brain regions compared between task performance and control states. Signals common for both states are typically not revealed. Previous motor learning studies have shown that extensive motor skill training can induce profound changes in regional activity in both task and control states. To address the issue of brain activity changes in the resting-state, we explored long-term motor training induced neuronal and physiological changes in normal human subjects using functional magnetic resonance imaging (fMRI) and positron emission tomography (PET). Ten healthy subjects performed a finger movement task daily for four weeks, during which three sessions of fMRI images and two sessions of PET images were acquired. Using a classical data analysis strategy, we found that the brain activation increased first and then returned to the pre-training, replicating previous findings. Interestingly, we also observed that motor skill training induced significant increases in regional cerebral blood flow (rCBF) in both task and resting states as the practice progressed. The apparent decrease in activation may actually result from a greater increase in activity in the resting state, rather than a decrease in the task state. By showing that training can affect the resting state, our findings have profound implications for the interpretation of functional activations in neuroimaging studies. Combining changes in resting state with activation data should greatly enhance our understanding of the mechanisms of motor-skill learning.

Contributions of the basal ganglia and functionally related brain structures to motor learning

This review discusses the cerebral plasticity, and the role of the cortico-striatal system in particular, observed as one is learning or planning to execute a newly learned motor behavior up to when the skill is consolidated or has become highly automatized. A special emphasis is given to imaging work describing the neural substrate mediating motor sequence learning and motor adaptation paradigms. These results are then put into a plausible neurobiological model of motor skill learning, which proposes an integrated view of the brain plasticity mediating this form of memory at different stages of the acquisition process.

Motor sequence learning and movement disorders

PURPOSE OF REVIEW

New insights into the psychophysiological determinants of performance changes and brain plasticity associated with motor sequence learning have recently been gained through behavioral and imaging studies in healthy individuals. In addition, using a variety of motor sequential paradigms in groups of patients affected by a movement disorder, major advances have been achieved in our understanding of the pathophysiological mechanisms underlying Parkinson's and Huntington's diseases, as well as primary forms of dystonia.

RECENT FINDINGS

This review begins by describing the latest findings in normal participants with regards to the dynamic alterations in neural networks observed across the different phases of motor sequence learning. It then focuses on the hotly debated issue of motor memory consolidation, highlighting the results of novel studies that investigated the role of both day and night sleep, the neural substrates and the developmental evolution mediating this process. Finally, this paper addresses current work looking at motor sequence learning in movement disorders that helps to better comprehend the functional contribution of basal ganglia structures to this type of memory, to assess the impact of such diseases on related patterns of brain activation, as well as to identify the neuronal compensatory mechanisms educed by these basal ganglia disorders.

SUMMARY

Such advances have major implications, not only for optimizing ways to learn new skilled behaviors in real-life situations, but also for guiding therapeutic approaches in patients with movement disorders.

Functional MRI of auditory responses in the zebra finch forebrain reveals a hierarchical organisation based on signal strength but not selectivity

BACKGROUND

Male songbirds learn their songs from an adult tutor when they are young. A network of brain nuclei known as the 'song system' is the likely neural substrate for sensorimotor learning and production of song, but the neural networks involved in processing the auditory feedback signals necessary for song learning and maintenance remain unknown. Determining which regions show preferential responsiveness to the bird's own song (BOS) is of great importance because neurons sensitive to self-generated vocalisations could mediate this auditory feedback process. Neurons in the song nuclei and in a secondary auditory area, the caudal medial mesopallium (CMM), show selective responses to the BOS. The aim of the present study is to investigate the emergence of BOS selectivity within the network of primary auditory sub-regions in the avian pallium.

METHODS AND FINDINGS

Using blood oxygen level-dependent (BOLD) fMRI, we investigated neural responsiveness to natural and manipulated self-generated vocalisations and compared the selectivity for BOS and conspecific song in different sub-regions of the thalamo-recipient area Field L. Zebra finch males were exposed to conspecific song, BOS and to synthetic variations on BOS that differed in spectro-temporal and/or modulation phase structure. We found significant differences in the strength of BOLD responses between regions L2a, L2b and CMM, but no inter-stimuli differences within regions. In particular, we have shown that the overall signal strength to song and synthetic variations thereof was different within two sub-regions of Field L2: zone L2a was significantly more activated compared to the adjacent sub-region L2b.

CONCLUSIONS

Based on our results we suggest that unlike nuclei in the song system, sub-regions in the primary auditory pallium do not show selectivity for the BOS, but appear to show different levels of activity with exposure to any sound according to their place in the auditory processing stream.

The power of spectral density analysis for mapping endogenous BOLD signal fluctuations

FMRI has revealed the presence of correlated low-frequency cerebro-vascular oscillations within functional brain systems, which are thought to reflect an intrinsic feature of large-scale neural activity. The spatial correlations shown by these fluctuations has been their identifying feature, distinguishing them from fluctuations associated with other processes. Major analysis methods characterize these correlations, identifying networks and their interactions with various factors. However, other analysis approaches are required to fully characterize the regional signal dynamics contributing to these correlations between regions. In this study we show that analysis of the power spectral density (PSD) of regional signals can identify changes in oscillatory dynamics across conditions, and is able to characterize the nature and spatial extent of signal changes underlying changes in measures of connectivity. We analyzed spectral density changes in sessions consisting of both resting-state scans and scans recording 2 min blocks of continuous unilateral finger tapping and rest. We assessed the relationship of PSD and connectivity measures by additionally tracking correlations between selected motor regions. Spectral density gradually increased in gray and white matter during the experiment. Finger tapping produced widespread decreases in low-frequency spectral density. This change was symmetric across the cortex, and extended beyond both the lateralized task-related signal increases, and the established "resting-state" motor network. Correlations between motor regions also reduced with task performance. In conclusion, analysis of PSD is a sensitive method for detecting and characterizing BOLD signal oscillations that can enhance the analysis of network connectivity.

Nonlinear estimation of the BOLD signal

Signal variations in functional Magnetic Resonance Imaging experiments essentially reflect the vascular system response to increased demand for oxygen caused by neuronal activity, termed the blood oxygenation level dependent (BOLD) effect. The most comprehensive model to date of the BOLD signal is formulated as a mixed continuous-discrete-time system of nonlinear stochastic differential equations. Previous approaches to the analysis of this system have been based on linearised approximations of the dynamics, which are limited in their ability to capture the inherent nonlinearities in the physiological system. In this paper we present a nonlinear filtering method for simultaneous estimation of the hidden physiological states and the system parameters, based on an iterative coordinate descent framework. State estimates of the cerebral blood flow, cerebral blood volume and deoxyhaemoglobin content are determined using a particle filter, demonstrated via simulation to be accurate, robust and efficient in comparison to linearisation-based techniques. The adaptive state and parameter estimation algorithm generates physiologically reasonable parameter estimates for experimental fMRI data. It is anticipated that signal processing techniques for modelling and estimation will become increasingly important in fMRI analyses as limitations of linear and linearised modelling are reached.