Remembering Forward: Neural Correlates of Memory and Prediction in Human Motor Adaptation

We used functional MR imaging (FMRI), a robotic manipulandum and systems identification techniques to examine neural correlates of predictive compensation for spring-like loads during goal-directed wrist movements in neurologically-intact humans. Although load changed unpredictably from one trial to the next, subjects nevertheless used sensorimotor memories from recent movements to predict and compensate upcoming loads. Prediction enabled subjects to adapt performance so that the task was accomplished with minimum effort. Population analyses of functional images revealed a distributed, bilateral network of cortical and subcortical activity supporting predictive load compensation during visual target capture. Cortical regions – including prefrontal, parietal and hippocampal cortices – exhibited trial-by-trial fluctuations in BOLD signal consistent with the storage and recall of sensorimotor memories or “states” important for spatial working memory. Bilateral activations in associative regions of the striatum demonstrated temporal correlation with the magnitude of kinematic performance error (a signal that could drive reward-optimizing reinforcement learning and the prospective scaling of previously learned motor programs). BOLD signal correlations with load prediction were observed in the cerebellar cortex and red nuclei (consistent with the idea that these structures generate adaptive fusimotor signals facilitating cancelation of expected proprioceptive feedback, as required for conditional feedback adjustments to ongoing motor commands and feedback error learning). Analysis of single subject images revealed that predictive activity was at least as likely to be observed in more than one of these neural systems as in just one. We conclude therefore that motor adaptation is mediated by predictive compensations supported by multiple, distributed, cortical and subcortical structures

The Brain is a Suitability Probability Processor: A macro model of our neural control system

Our world is characterized by growing diversity and complexity, and the effort to manage our affairs in a good way becomes increasingly difficult. This is true for all spheres of life, including culture, economy, technology, science, politics, environment and daily grind. A corresponding development occurs to our understanding of the brain, which is the crucial organ to keep track of everything. The amount of domain specific findings about this organ grows dramatically, what takes preferably place by highly specialized research. But the holistic understanding of the brain is rather more challenged than supported by this development, resulting in a huge lack of knowledge on the systemic level of the neurosciences. Eckhard Schindler faces this dilemma by introducing a macro model of the brain. This is not only an attempt to improve the perception of our most crucial organ, but also to open a door for a better understanding of our species and for ease our life again.:Part 1 - The Brain as Suitability Probability Processor Introduction Neuro basics Purpose, perception and motor control Excitation, inhibition, pattern transformation and circuits Memory Homeostasis, pain, emotions and rewards The SPP model The emoti(onal-moti)vational system The control levels of the central nervous system The attention assessment controller (AAC) Efficiency through delegation and structuring Universal suitability probability evaluation Needs and library of associative-emotivational patterns Higher needs Needs and suitability probability evaluation Suitability probability evaluation and evolution The two types of consciousness Conscious experiences Individual and social consciousness The 4DI model A four-dimensional intelligence concept (4DI) Dynamics of the need hierarchy Social emotivational dependency chains The need for coherence Artificial needs versus growth needs Dynamics in the 3D tension field 3D tensions in the affluent society The tunnel vision paradox Emotivational amplification adaptation Fading consciousness in affluent contexts About the integrative ingredient of 4DI Toe-holds for other disciplines Part 2 - Excursions to the current state of science Introduction Basal ganglia (BG) and frontal cortex Emotion, motivation and memory Cognitive control and emotions Consciousness Psychology Brain and computer The biggest open questions Index of figures Index of tables Reference

Multiple Motor Learning Processes in Humans: Defining Their Neurophysiological Bases

Learning new motor behaviors or adjusting previously learned actions to account for dynamic changes in our environment requires the operation of multiple distinct motor learning processes, which rely on different neuronal substrates. For instance, humans are capable of acquiring new motor patterns via the formation of internal model representations of the movement dynamics and through positive reinforcement. In this review, we will discuss how changes in human physiological markers, assessed with noninvasive brain stimulation techniques from distinct brain regions, can be utilized to provide insights toward the distinct learning processes underlying motor learning. We will summarize the findings from several behavioral and neurophysiological studies that have made efforts to understand how distinct processes contribute to and interact when learning new motor behaviors. In particular, we will extensively review two types of behavioral processes described in human sensorimotor learning: (1) a recalibration process of a previously learned movement and (2) acquiring an entirely new motor control policy, such as learning to play an instrument. The selected studies will demonstrate in-detail how distinct physiological mechanisms contributions change depending on the time course of learning and the type of behaviors being learned

Neurosystems: brain rhythms and cognitive processing

Neuronal rhythms are ubiquitous features of brain dynamics, and are highly correlated with cognitive processing. However, the relationship between the physiological mechanisms producing these rhythms and the functions associated with the rhythms remains mysterious. This article investigates the contributions of rhythms to basic cognitive computations (such as filtering signals by coherence and/or frequency) and to major cognitive functions (such as attention and multi-modal coordination). We offer support to the premise that the physiology underlying brain rhythms plays an essential role in how these rhythms facilitate some cognitive operations.098352 - Wellcome Trust; 5R01NS067199 - NINDS NIH HH

Phonatory and articulatory representations of speech production in cortical and subcortical fMRI responses

Speaking involves coordination of multiple neuromotor systems, including respiration, phonation and articulation. Developing non-invasive imaging methods to study how the brain controls these systems is critical for understanding the neurobiology of speech production. Recent models and animal research suggest that regions beyond the primary motor cortex (M1) help orchestrate the neuromotor control needed for speaking, including cortical and sub-cortical regions. Using contrasts between speech conditions with controlled respiratory behavior, this fMRI study investigates articulatory gestures involving the tongue, lips and velum (i.e., alveolars versus bilabials, and nasals versus orals), and phonatory gestures (i.e., voiced versus whispered speech). Multivariate pattern analysis (MVPA) was used to decode articulatory gestures in M1, cerebellum and basal ganglia. Furthermore, apart from confirming the role of a mid-M1 region for phonation, we found that a dorsal M1 region, linked to respiratory control, showed significant differences for voiced compared to whispered speech despite matched lung volume observations. This region was also functionally connected to tongue and lip M1 seed regions, underlying its importance in the coordination of speech. Our study confirms and extends current knowledge regarding the neural mechanisms underlying neuromotor speech control, which hold promise to study neural dysfunctions involved in motor-speech disorders non-invasively.Tis work was supported by the Spanish Ministry of Economy and Competitiveness through the Juan de la Cierva Fellowship (FJCI-2015-26814), and the Ramon y Cajal Fellowship (RYC-2017- 21845), the Spanish State Research Agency through the BCBL “Severo Ochoa” excellence accreditation (SEV-2015-490), the Basque Government (BERC 2018- 2021) and the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant (No 799554).info:eu-repo/semantics/publishedVersio