Revealing neural representations of movements and skill using multi voxel pattern analysis

One of the main functions of the human brain is to process information, such that we can interact efficiently with our environment by moving our body. Neuronal representations of information pertaining to the movement is fundamental for control. Using functional magnetic resonance imaging, researchers have studied brain areas that are responsible for motor control based on overall neuronal signal changes. It is assumed that the amount of overall activity indicates how much an area is involved in the control of movements. In this thesis, I start from the approach that the representation of critical variables describing the movements, rather than the overall activation, is the most relevant factor for a region to be important in the control of an action. Representations in three major fields of motor control were studied in this thesis. First, the integration of sensory and motor information was analysed via finger representations in the cerebellum and the neocortex. The findings suggest that sensory and motor representations of fingers overlap spatially in the neocortex but are interdigitated in the cerebellum, suggesting neuronal differences in how information are integrated in the brain structures. Then, neuronal reorganisations of representations were studied during motor learning. The results showed that the neural representation of sequences becomes more distinct with training, while the overall activity does not change. Lastly, I studied effector specific and effector independent representations of sequential motor behaviours by investigating the similarity of neuronal representations for left and right hand performance. Overall, this thesis demonstrates that the study of neural representations using multivariate methods in fMRI provides a new hypothesis-driven approach to the study of human motor control and learning of movements

A multivariate method to determine the dimensionality of neural representation from population activity.

How do populations of neurons represent a variable of interest? The notion of feature spaces is a useful concept to approach this question: According to this model, the activation patterns across a neuronal population are composed of different pattern components. The strength of each of these components varies with one latent feature, which together are the dimensions along which the population represents the variable. Here we propose a new method to determine the number of feature dimensions that best describes the activation patterns. The method is based on Gaussian linear classifiers that use only the first d most important pattern dimensions. Using cross-validation, we can identify the classifier that best matches the dimensionality of the neuronal representation. We test this method on two datasets of motor cortical activation patterns measured with functional magnetic resonance imaging (fMRI), during (i) simultaneous presses of all fingers of a hand at different force levels and (ii) presses of different individual fingers at a single force level. As expected, the new method shows that the representation of force is low-dimensional; the neural activation for different force levels is scaled versions of each other. In comparison, individual finger presses are represented in a full, four-dimensional feature space. The approach can be used to determine an important characteristic of neuronal population codes without knowing the form of the underlying features. It therefore provides a novel tool in the building of quantitative models of neuronal population activity as measured with fMRI or other approaches

Two Distinct Ipsilateral Cortical Representations for Individuated Finger Movements.

Movements of the upper limb are controlled mostly through the contralateral hemisphere. Although overall activity changes in the ipsilateral motor cortex have been reported, their functional significance remains unclear. Using human functional imaging, we analyzed neural finger representations by studying differences in fine-grained activation patterns for single isometric finger presses. We demonstrate that cortical motor areas encode ipsilateral movements in 2 fundamentally different ways. During unimanual ipsilateral finger presses, primary sensory and motor cortices show, underneath global suppression, finger-specific activity patterns that are nearly identical to those elicited by contralateral mirror-symmetric action. This component vanishes when both motor cortices are functionally engaged during bimanual actions. We suggest that the ipsilateral representation present during unimanual presses arises because otherwise functionally idle circuits are driven by input from the opposite hemisphere. A second type of representation becomes evident in caudal premotor and anterior parietal cortices during bimanual actions. In these regions, ipsilateral actions are represented as nonlinear modulation of activity patterns related to contralateral actions, an encoding scheme that may provide the neural substrate for coordinating bimanual movements. We conclude that ipsilateral cortical representations change their informational content and functional role, depending on the behavioral context

SHORT COMMUNICATION: Complementary tumor induction in neural grafts exposed to N-ethyl-N-nitrosourea and an activated myc gene

Using a combination of transplacental carcinogen exposure and retrovirus-mediated oncogene transfer into fetal brain transplants, we have studied complementary transformation by N-ethyl-N-nitrosourea (NEU) and the v-myc oncogene in the nervous system. Previous experiments had demonstrated that both agents will not induce tumors independently whereas simultaneous expression of v-H-ras and v-gag/myc exerted a powerful transforming potential in neural grafts. In order to identify other genetic alterations that co-operate with an activated myc gene, the neurotropic carcinogen NEU was used to generate mutations of cellular genes. On embryonic day 14 (ED14), pregnant donor animals (F344 rats) received a single i.v. dose of NEU (50 mg/kg). Twenty-four hours later (ED15), the fetal brains were removed, triturated and incubated with a retroviral vector carrying the v-gag/myc oncogene. Subsequently, these primary cell suspensions were transplanted stereotactically into the caudate-putamen of syngenic adult recipients. After latency periods of 3-6 months, 5 of 10 recipients harboring ED15 fetal brain transplants developed malignant, poorly differentiated neuroectodermal tumors in the grafts. No tumor development was observed in seven recipients harboring ED16 neural grafts. Cell lines were established from three tumors and the 110 kd gag/myc fusion protein encoded by the retroviral construct was identified in the tumors by Western blotting. Several candidate genes for mutational activation by NEU including the H-ras, K-ras and neu oncogenes were analyzed for specific point mutations by polymerase chain reaction (PCR) and direct DNA sequencing of the PCR products. However, no mutations were found in any of these genes. These findings lend further support to the multistep hypothesis of neoplastic transformation in the brain. The tumors induced in this model provide an interesting tool for the identification of genes that co-operate with an activated myc gene in neurocarcinogenesi

Intact finger representation within primary sensorimotor cortex of musician's dystonia.

Musician's dystonia presents with a persistent deterioration of motor control during musical performance. A predominant hypothesis has been that this is underpinned by maladaptive neural changes to the somatotopic organisation of finger representations within primary somatosensory cortex. Here, we tested this hypothesis by investigating the finger-specific activity patterns in the primary somatosensory and motor cortex using functional MRI and multivariate pattern analysis in nine musicians with dystonia and nine healthy musicians. A purpose-built keyboard device allowed characterisation of activity patterns elicited during passive extension and active finger presses of individual fingers. We analysed the data using both traditional spatial analysis and state-of-the art multivariate analyses. Our analysis reveals that digit representations in musicians were poorly captured by spatial analyses. An optimised spatial metric found clear somatotopy but no difference in the spatial geometry between fingers with dystonia. Representational similarity analysis was confirmed as a more reliable technique than all spatial metrics evaluated. Significantly, the dissimilarity architecture was equivalent for musicians with and without dystonia. No expansion or spatial shift of digit representation maps were found in the symptomatic group. Our results therefore suggest that the neural representation of generic finger maps in primary sensorimotor cortex is intact in musician's dystonia. These results speak against the idea that task-specific dystonia is associated with a distorted hand somatotopy and lend weight to an alternative hypothesis that task-specific dystonia is due to a higher order disruption of skill encoding. Such a formulation can better explain the task-specific deficit and offers alternative inroads for therapeutic interventions

Boundaries of task-specificity: bimanual finger dexterity is reduced in musician's dystonia.

Task-specific dystonia leads to loss of sensorimotor control for a particular motor skill. Although focal in nature, it is hugely disabling and can terminate professional careers in musicians. Biomarkers for underlying mechanism and severity are much needed. In this study, we designed a keyboard device that measured the forces generated at all fingertips during individual finger presses. By reliably quantifying overflow to other fingers in the instructed (enslaving) and contralateral hand (mirroring) we explored whether this task could differentiate between musicians with and without dystonia. 20 right-handed professional musicians (11 with dystonia) generated isometric flexion forces with the instructed finger to match 25%, 50% or 75% of maximal voluntary contraction for that finger. Enslaving was estimated as a linear slope of the forces applied across all instructed/uninstructed finger combinations. Musicians with dystonia had a small but robust loss of finger dexterity. There was increased enslaving and mirroring, primarily during use of the symptomatic hand (enslaving p = 0.003; mirroring p = 0.016), and to a lesser extent with the asymptomatic hand (enslaving p = 0.052; mirroring p = 0.062). Increased enslaving and mirroring were seen across all combinations of finger pairs. In addition, enslaving was exaggerated across symptomatic fingers when more than one finger was clinically affected. Task-specific dystonia therefore appears to express along a gradient, most severe in the affected skill with subtle and general motor control dysfunction in the background. Recognition of this provides a more nuanced understanding of the sensorimotor control deficits at play and can inform therapeutic options for this highly disabling disorder

Inhibition of N1-Src kinase by a specific SH3 peptide ligand reveals a role for N1-Src in neurite elongation by L1-CAM

In the mammalian brain the ubiquitous tyrosine kinase, C-Src, undergoes splicing to insert short sequences in the SH3 domain to yield N1- and N2-Src. We and others have previously shown that the N-Srcs have altered substrate specificity and kinase activity compared to C-Src. However, the exact functions of the N-Srcs are unknown and it is likely that N-Src signalling events have been misattributed to C-Src because they cannot be distinguished by conventional Src inhibitors that target the kinase domain. By screening a peptide phage display library, we discovered a novel ligand (PDN1) that targets the unique SH3 domain of N1-Src and inhibits N1-Src in cells. In cultured neurons, PDN1 fused to a fluorescent protein inhibited neurite outgrowth, an effect that was mimicked by shRNA targeting the N1-Src microexon. PDN1 also inhibited L1-CAM-dependent neurite elongation in cerebellar granule neurons, a pathway previously shown to be disrupted in Src(−/−) mice. PDN1 therefore represents a novel tool for distinguishing the functions of N1-Src and C-Src in neurons and is a starting point for the development of a small molecule inhibitor of N1-Src

A for-loop is all you need. For solving the inverse problem in the case of personalized tumor growth modeling

Solving the inverse problem is the key step in evaluating the capacity of a physical model to describe real phenomena. In medical image computing, it aligns with the classical theme of image-based model personalization. Traditionally, a solution to the problem is obtained by performing either sampling or variational inference based methods. Both approaches aim to identify a set of free physical model parameters that results in a simulation best matching an empirical observation. When applied to brain tumor modeling, one of the instances of image-based model personalization in medical image computing, the overarching drawback of the methods is the time complexity of finding such a set. In a clinical setting with limited time between imaging and diagnosis or even intervention, this time complexity may prove critical. As the history of quantitative science is the history of compression (Schmidhuber and Fridman, 2018), we align in this paper with the historical tendency and propose a method compressing complex traditional strategies for solving an inverse problem into a simple database query task. We evaluated different ways of performing the database query task assessing the trade-off between accuracy and execution time. On the exemplary task of brain tumor growth modeling, we prove that the proposed method achieves one order speed-up compared to existing approaches for solving the inverse problem. The resulting compute time offers critical means for relying on more complex and, hence, realistic models, for integrating image preprocessing and inverse modeling even deeper, or for implementing the current model into a clinical workflow. The code is available at https://github.com/IvanEz/for-loop-tumor