Perception, cognition, and action in hyperspaces: implications on brain plasticity, learning, and cognition

We live in a three-dimensional (3D) spatial world; however, our retinas receive a pair of 2D projections of the 3D environment. By using multiple cues, such as disparity, motion parallax, perspective, our brains can construct 3D representations of the world from the 2D projections on our retinas. These 3D representations underlie our 3D perceptions of the world and are mapped into our motor systems to generate accurate sensorimotor behaviors. Three-dimensional perceptual and sensorimotor capabilities emerge during development: the physiology of the growing baby changes hence necessitating an ongoing re-adaptation of the mapping between 3D sensory representations and the motor coordinates. This adaptation continues in adulthood and is quite general to successfully deal with joint-space changes (longer arms due to growth), skull and eye size changes (and still being able of accurate eye movements), etc. A fundamental question is whether our brains are inherently limited to 3D representations of the environment because we are living in a 3D world, or alternatively, our brains may have the inherent capability and plasticity of representing arbitrary dimensions; however, 3D representations emerge from the fact that our development and learning take place in a 3D world. Here, we review research related to inherent capabilities and limitations of brain plasticity in terms of its spatial representations and discuss whether with appropriate training, humans can build perceptual and sensorimotor representations of spatial 4D environments, and how the presence or lack of ability of a solid and direct 4D representation can reveal underlying neural representations of space.Published versio

Training locomotor networks

For a complete adult spinal rat to regain some weight-bearing stepping capability, it appears that a sequence of specific proprioceptive inputs that are similar, but not identical, from step to step must be generated over repetitive step cycles. Furthermore, these cycles must include the activation of specific neural circuits that are intrinsic to the lumbosacral spinal cord segments. For these sensorimotor pathways to be effective in generating stepping, the spinal circuitry must be modulated to an appropriate excitability level. This level of modulation is sustained from supraspinal input in intact, but not spinal, rats. In a series of experiments with complete spinal rats, we have shown that an appropriate level of excitability of the spinal circuitry can be achieved using widely different means. For example, this modulation level can be acquired pharmacologically, via epidural electrical stimulation over specific lumbosacral spinal cord segments, and/or by use-dependent mechanisms such as step or stand training. Evidence as to how each of these treatments can “tune” the spinal circuitry to a “physiological state” that enables it to respond appropriately to proprioceptive input will be presented. We have found that each of these interventions can enable the proprioceptive input to actually control extensive details that define the dynamics of stepping over a range of speeds, loads, and directions. A series of experiments will be described that illustrate sensory control of stepping and standing after a spinal cord injury and the necessity for the “physiological state” of the spinal circuitry to be modulated within a critical window of excitability for this control to be manifested. The present findings have important consequences not only for our understanding of how the motor pattern for stepping is formed, but also for the design of rehabilitation intervention to restore lumbosacral circuit function in humans following a spinal cord injury

Pre- and Post-alpha Motoneuronal Control of the Soleus H-reflex during Sinusoidal Hip Movements in Human Spinal Cord Injury

The aim of this study was to establish the contribution of hip-mediated sensory feedback to spinal interneuronal circuits during dynamic conditions in people with incomplete spinal cord injury (SCI). Specifically, we investigated the effects of synergistic and antagonistic group I afferents on the soleus H-reflex during imposed sinusoidal hip movements. The soleus H-reflex was conditioned by stimulating the common peroneal nerve (CPN) at short (2, 3, and 4 ms) and long (80, 100, and 120 ms) conditioning test (C-T) intervals to assess the reciprocal and pre-synaptic inhibition of the soleus H-reflex, respectively. The soleus H-reflex was also conditioned by medial gastrocnemius (MG) nerve stimulation at C-T intervals ranging from 4 to 7 ms to assess changes in autogenic Ib inhibition during hip movement. Sinusoidal hip movements were imposed to the right hip joint at 0.2 Hz by the Biodex system while subjects were supine. The effects of sinusoidal hip movement on five leg muscles along with hip, knee, and ankle joint torques were also established during sensorimotor conditioning of the reflex. Phase-dependent modulation of antagonistic and synergistic muscle afferents was present during hip movement, with the reciprocal, pre-synaptic, and Ib inhibition to be significantly reduced during hip extension and reinforced during hip flexion. Reflexive muscle and joint torque responses – induced by the hip movement – were entrained to specific phases of hip movement. This study provides evidence that hip-mediated input acts as a controlling signal of pre- and post-alpha motoneuronal control of the soleus H-reflex. The expression of these spinal interneuronal circuits during imposed sinusoidal hip movements is discussed with respect to motor recovery in humans after SCI

Neural Control of Actions Involving Different Coordinate Systems

di Parm

Functional connectivity and neuronal dynamics: insights from computational methods

International audienceBrain functions rely on flexible communication between microcircuits in distinct cortical regions. The mechanisms underlying flexible information routing are still, however, largely unknown. Here, we hypothesize that the emergence of a multiplicity of possible information routing patterns is due to the richness of the complex dynamics that can be supported by an underlying structural network. Analyses of circuit computational models of interacting brain areas suggest that different dynamical states associated with a given connectome mechanistically implement different information routing patterns between system's components. As a result, a fast, network-wide and self-organized reconfiguration of information routing patterns-and Functional Connectivity networks, seen as their proxy-can be achieved by inducing a transition between the available intrinsic dynamical states. We present here a survey of theoretical and modelling results, as well as of sophisticated metrics of Functional Connectivity which are compliant with the daunting task of characterizing dynamic routing from neural data. Theory: Function follows dynamics, rather than structure Neuronal activity conveys information, but which target should this information be-pushed‖ to, or which source should new information be-pulled‖ from? The problem of dynamic information routing is ubiquitous in a distributed information processing system as the brain. Brain functions in general require the control of distributed networks of interregional communication on fast timescales compliant with behavior, but incompatible with plastic modifications of connectivity tracts (Bressler & Kelso, 2001; Varela et al., 2001). This argument led to notions of connectivity based on information exchange-or more generically, an-interaction‖-between brain regions or neuronal populations, rather than based on the underlying STRUCTURAL CONNECTIVITY (SC, i.e. anatomic). An entire zoo of data-driven metrics has been introduced in the literature and this chapter will review some of them. Notwithstanding, they track simple correlation, or directed causal influence (Friston, 2011) or information transfer (Wibral et al., 2014) between time-series of activity. Thes

Interaction dynamics and autonomy in cognitive systems

The concept of autonomy is of crucial importance for understanding life and cognition. Whereas cellular and organismic autonomy is based in the self-production of the material infrastructure sustaining the existence of living beings as such, we are interested in how biological autonomy can be expanded into forms of autonomous agency, where autonomy as a form of organization is extended into the behaviour of an agent in interaction with its environment (and not its material self-production). In this thesis, we focus on the development of operational models of sensorimotor agency, exploring the construction of a domain of interactions creating a dynamical interface between agent and environment. We present two main contributions to the study of autonomous agency: First, we contribute to the development of a modelling route for testing, comparing and validating hypotheses about neurocognitive autonomy. Through the design and analysis of specific neurodynamical models embedded in robotic agents, we explore how an agent is constituted in a sensorimotor space as an autonomous entity able to adaptively sustain its own organization. Using two simulation models and different dynamical analysis and measurement of complex patterns in their behaviour, we are able to tackle some theoretical obstacles preventing the understanding of sensorimotor autonomy, and to generate new predictions about the nature of autonomous agency in the neurocognitive domain. Second, we explore the extension of sensorimotor forms of autonomy into the social realm. We analyse two cases from an experimental perspective: the constitution of a collective subject in a sensorimotor social interactive task, and the emergence of an autonomous social identity in a large-scale technologically-mediated social system. Through the analysis of coordination mechanisms and emergent complex patterns, we are able to gather experimental evidence indicating that in some cases social autonomy might emerge based on mechanisms of coordinated sensorimotor activity and interaction, constituting forms of collective autonomous agency

Rediscovering Richard Held: Activity and Passivity in Perceptual Learning

Understanding the role of self-generated movements in perceptual learning is central to action-based theories of perception. Pioneering work on sensory adaptation by Richard M. Held during the 1950s and 1960s can still shed light on this question. In a variety of rich experiments Held and his team demonstrated the need for self-generated movements in sensory adaptation and perceptual learning. This body of work received different critical interpretations, was then forgotten for some time, and saw a surge of revived interest within embodied cognitive science. Through a brief review of Held’s work and reactions to it, we seek to contribute to discussions on the role of activity and passivity in perceptual learning. We classify different positions according to whether this role is considered to be contextual (facilitatory, but not necessary), enabling (causally necessary), or constitutive (an inextricable part of the learning process itself). We also offer a critique of the notions of activity and passivity and how they are operationalized in experimental studies. The active-passive distinction is not a binary but involves a series of dimensions and relative degrees that can make it difficult to interpret and replicate experimental results. We introduce three of these dimensions drawing on work on the sense of agency: action initiation, control, and monitoring. These refinements in terms of causal relations and dimensions of activity-passivity should help illuminate open questions concerning the role of activity in perception and perceptual learning and clarify the convergences and differences between enaction and ecological psychology.Fil: Bermejo, Fernando Raul. Universidad Nacional de Córdoba. Facultad de Psicología; Argentina. Universidad Nacional de Córdoba. Facultad de Arquitectura, Urbanismo y Diseño. Centro de Investigaciones Acusticas y Luminotécnicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; ArgentinaFil: Hug, Mercedes Ximena. Universidad Nacional de Córdoba. Facultad de Psicología; Argentina. Universidad Nacional de Córdoba. Facultad de Arquitectura, Urbanismo y Diseño. Centro de Investigaciones Acusticas y Luminotécnicas; ArgentinaFil: Di Paolo, Ezequiel Alejandro. Universidad del País Vasco; España. University of Sussex; Reino Unido. Ikerbasque; España. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

Nonlinear brain dynamics as macroscopic manifestation of underlying many-body field dynamics

Neural activity patterns related to behavior occur at many scales in time and space from the atomic and molecular to the whole brain. Here we explore the feasibility of interpreting neurophysiological data in the context of many-body physics by using tools that physicists have devised to analyze comparable hierarchies in other fields of science. We focus on a mesoscopic level that offers a multi-step pathway between the microscopic functions of neurons and the macroscopic functions of brain systems revealed by hemodynamic imaging. We use electroencephalographic (EEG) records collected from high-density electrode arrays fixed on the epidural surfaces of primary sensory and limbic areas in rabbits and cats trained to discriminate conditioned stimuli (CS) in the various modalities. High temporal resolution of EEG signals with the Hilbert transform gives evidence for diverse intermittent spatial patterns of amplitude (AM) and phase modulations (PM) of carrier waves that repeatedly re-synchronize in the beta and gamma ranges at near zero time lags over long distances. The dominant mechanism for neural interactions by axodendritic synaptic transmission should impose distance-dependent delays on the EEG oscillations owing to finite propagation velocities. It does not. EEGs instead show evidence for anomalous dispersion: the existence in neural populations of a low velocity range of information and energy transfers, and a high velocity range of the spread of phase transitions. This distinction labels the phenomenon but does not explain it. In this report we explore the analysis of these phenomena using concepts of energy dissipation, the maintenance by cortex of multiple ground states corresponding to AM patterns, and the exclusive selection by spontaneous breakdown of symmetry (SBS) of single states in sequences.Comment: 31 page

Cortical Dynamics of Language

The human capability for fluent speech profoundly directs inter-personal communication and, by extension, self-expression. Language is lost in millions of people each year due to trauma, stroke, neurodegeneration, and neoplasms with devastating impact to social interaction and quality of life. The following investigations were designed to elucidate the neurobiological foundation of speech production, building towards a universal cognitive model of language in the brain. Understanding the dynamical mechanisms supporting cortical network behavior will significantly advance the understanding of how both focal and disconnection injuries yield neurological deficits, informing the development of therapeutic approaches