Space, Time and Learning in the Hippocampus: How Fine Spatial and Temporal Scales Are Expanded into Population Codes for Behavioral Control

The hippocampus participates in multiple functions, including spatial navigation, adaptive timing, and declarative (notably, episodic) memory. How does it carry out these particular functions? The present article proposes that hippocampal spatial and temporal processing are carried out by parallel circuits within entorhinal cortex, dentate gyrus, and CA3 that are variations of the same circuit design. In particular, interactions between these brain regions transform fine spatial and temporal scales into population codes that are capable of representing the much larger spatial and temporal scales that are needed to control adaptive behaviors. Previous models of adaptively timed learning propose how a spectrum of cells tuned to brief but different delays are combined and modulated by learning to create a population code for controlling goal-oriented behaviors that span hundreds of milliseconds or even seconds. Here it is proposed how projections from entorhinal grid cells can undergo a similar learning process to create hippocampal place cells that can cover a space of many meters that are needed to control navigational behaviors. The suggested homology between spatial and temporal processing may clarify how spatial and temporal information may be integrated into an episodic memory.

Towards a Unified Theory of Neocortex: Laminar Cortical Circuits for Vision and Cognition

A key goal of computational neuroscience is to link brain mechanisms to behavioral functions. The present article describes recent progress towards explaining how laminar neocortical circuits give rise to biological intelligence. These circuits embody two new and revolutionary computational paradigms: Complementary Computing and Laminar Computing. Circuit properties include a novel synthesis of feedforward and feedback processing, of digital and analog processing, and of pre-attentive and attentive processing. This synthesis clarifies the appeal of Bayesian approaches but has a far greater predictive range that naturally extends to self-organizing processes. Examples from vision and cognition are summarized. A LAMINART architecture unifies properties of visual development, learning, perceptual grouping, attention, and 3D vision. A key modeling theme is that the mechanisms which enable development and learning to occur in a stable way imply properties of adult behavior. It is noted how higher-order attentional constraints can influence multiple cortical regions, and how spatial and object attention work together to learn view-invariant object categories. In particular, a form-fitting spatial attentional shroud can allow an emerging view-invariant object category to remain active while multiple view categories are associated with it during sequences of saccadic eye movements. Finally, the chapter summarizes recent work on the LIST PARSE model of cognitive information processing by the laminar circuits of prefrontal cortex. LIST PARSE models the short-term storage of event sequences in working memory, their unitization through learning into sequence, or list, chunks, and their read-out in planned sequential performance that is under volitional control. LIST PARSE provides a laminar embodiment of Item and Order working memories, also called Competitive Queuing models, that have been supported by both psychophysical and neurobiological data. These examples show how variations of a common laminar cortical design can embody properties of visual and cognitive intelligence that seem, at least on the surface, to be mechanistically unrelated.

Adaptive Neural Networks for Control of Movement Trajectories Invariant under Speed and Force Rescaling

This article describes two neural network modules that form part of an emerging theory of how adaptive control of goal-directed sensory-motor skills is achieved by humans and other animals. The Vector-Integration-To-Endpoint (VITE) model suggests how synchronous multi-joint trajectories are generated and performed at variable speeds. The Factorization-of-LEngth-and-TEnsion (FLETE) model suggests how outflow movement commands from a VITE model may be performed at variable force levels without a loss of positional accuracy. The invariance of positional control under speed and force rescaling sheds new light upon a familiar strategy of motor skill development: Skill learning begins with performance at low speed and low limb compliance and proceeds to higher speeds and compliances. The VITE model helps to explain many neural and behavioral data about trajectory formation, including data about neural coding within the posterior parietal cortex, motor cortex, and globus pallidus, and behavioral properties such as Woodworth's Law, Fitts Law, peak acceleration as a function of movement amplitude and duration, isotonic arm movement properties before and after arm-deafferentation, central error correction properties of isometric contractions, motor priming without overt action, velocity amplification during target switching, velocity profile invariance across different movement distances, changes in velocity profile asymmetry across different movement durations, staggered onset times for controlling linear trajectories with synchronous offset times, changes in the ratio of maximum to average velocity during discrete versus serial movements, and shared properties of arm and speech articulator movements. The FLETE model provides new insights into how spina-muscular circuits process variable forces without a loss of positional control. These results explicate the size principle of motor neuron recruitment, descending co-contractive compliance signals, Renshaw cells, Ia interneurons, fast automatic reactive control by ascending feedback from muscle spindles, slow adaptive predictive control via cerebellar learning using muscle spindle error signals to train adaptive movement gains, fractured somatotopy in the opponent organization of cerebellar learning, adaptive compensation for variable moment-arms, and force feedback from Golgi tendon organs. More generally, the models provide a computational rationale for the use of nonspecific control signals in volitional control, or "acts of will", and of efference copies and opponent processing in both reactive and adaptive motor control tasks.

Cortical Dynamics of Feature Binding and Reset: Control of Visual Persistence

An analysis of the reset of visual cortical circuits responsible for the binding or segmentation of visual features into coherent visual forms yields a model that explains properties of visual persistence. The reset mechanisms prevent massive smearing or visual percepts in response to rapidly moving images. The model simulates relationships among psychophysical data showing inverse relations of persistence to flash luminance and duration, greaterr persistence of illusory contours than real contours, a U-shaped temporal function for persistence of illusory contours, a reduction of persistence: due to adaptation with a stimulus of like orientation, an increase or persistence due to adaptation with a stimulus of perpendicular orientation, and an increase of persistence with spatial separation of a masking stimulus. The model suggests that a combination of habituative, opponent, and endstopping mechanisms prevent smearing and limit persistence. Earlier work with the model has analyzed data about boundary formation, texture segregation, shape-from-shading, and figure-ground separation. Thus, several types of data support each model mechanism and new predictions are made.

Oscillations by minimal bacterial suicide circuits reveal hidden facets of host-circuit physiology.

Synthetic biology seeks to enable programmed control of cellular behavior though engineered biological systems. These systems typically consist of synthetic circuits that function inside, and interact with, complex host cells possessing pre-existing metabolic and regulatory networks. Nevertheless, while designing systems, a simple well-defined interface between the synthetic gene circuit and the host is frequently assumed. We describe the generation of robust but unexpected oscillations in the densities of bacterium Escherichia coli populations by simple synthetic suicide circuits containing quorum components and a lysis gene. Contrary to design expectations, oscillations required neither the quorum sensing genes (luxR and luxI) nor known regulatory elements in the P(luxI) promoter. Instead, oscillations were likely due to density-dependent plasmid amplification that established a population-level negative feedback. A mathematical model based on this mechanism captures the key characteristics of oscillations, and model predictions regarding perturbations to plasmid amplification were experimentally validated. Our results underscore the importance of plasmid copy number and potential impact of "hidden interactions" on the behavior of engineered gene circuits - a major challenge for standardizing biological parts. As synthetic biology grows as a discipline, increasing value may be derived from tools that enable the assessment of parts in their final context.

Frontal-striatal circuits in cognitive aging: Evidence for caudate involvement

Changes in cognition with aging have been claimed to be due in large part to a decline in frontal lobe function. However, at our present state of knowledge, the emphasis on the frontal lobes to the exclusion of the rest of the frontal-striatal circuits of which they are a part is unwarranted. To argue this point, I consider another anatomical candidate within these circuits, the caudate. Evidence is presented that the caudate decreases in size with age as much as the frontal lobes and that damage to either the frontal lobes or the caudate is accompanied by declines in inhibitory processes, executive control, and cognitive speed similar to those seen in normal aging. Separating the unique contributions of the frontal lobes and the caudate to these circuits is difficult but should be the focus of future studies of the biological basis of cognitive aging.

Cognitive control of movement via the cerebellar-recipient thalamus.

The cognitive control of behavior was long considered to be centralized in cerebral cortex. More recently, subcortical structures such as cerebellum and basal ganglia have been implicated in cognitive functions as well. The fact that subcortico-cortical circuits for the control of movement involve the thalamus prompts the notion that activity in movement-related thalamus may also reflect elements of cognitive behavior. Yet this hypothesis has rarely been investigated. Using the pathways linking cerebellum to cerebral cortex via the thalamus as a template, we review evidence that the motor thalamus, together with movement-related central thalamus have the requisite connectivity and activity to mediate cognitive aspects of movement control.

How position, velocity, and temporal information combine in the prospective control of catching:data and model

The cerebral cortex contains circuitry for continuously computing properties of the environment and one's body, as well as relations among those properties. The success of complex perceptuomotor performances requires integrated, simultaneous use of such relational information. Ball catching is a good example as it involves reaching and grasping of visually pursued objects that move relative to the catcher. Although integrated neural control of catching has received sparse attention in the neuroscience literature, behavioral observations have led to the identification of control principles that may be embodied in the involved neural circuits. Here, we report a catching experiment that refines those principles via a novel manipulation. Visual field motion was used to perturb velocity information about balls traveling on various trajectories relative to a seated catcher, with various initial hand positions. The experiment produced evidence for a continuous, prospective catching strategy, in which hand movements are planned based on gaze-centered ball velocity and ball position information. Such a strategy was implemented in a new neural model, which suggests how position, velocity, and temporal information streams combine to shape catching movements. The model accurately reproduces the main and interaction effects found in the behavioral experiment and provides an interpretation of recently observed target motion-related activity in the motor cortex during interceptive reaching by monkeys. It functionally interprets a broad range of neurobiological and behavioral data, and thus contributes to a unified theory of the neural control of reaching to stationary and moving targets.

An Adaptive Predictive Control Strategy for RMPPT under Partially Shaded Conditions

As one of key technologies in photovoltaic converter control, Maximum Power Point Tracking (MPPT) methods can keep the power conversion efficiency as high as nearly 99% under the uniform solar irradiance condition. However, these methods may fail when shading conditions occur and the power loss can over as much as 70% due to the multiple maxima in curve in shading conditions v.s. single maximum point in uniformly solar irradiance. In this paper, a Real Maximum Power Point Tracking (RMPPT) strategy under Partially Shaded Conditions (PSCs) is introduced to deal with this kind of problems. An optimization problem, based on a predictive model which will change adaptively with environment, is developed to tracking the global maxima and corresponding adaptive control strategy is presented. No additional circuits are required to obtain the environment uncertainties. Finally, simulations show the effectiveness of proposed method.

Design and evaluation of multi-band RF energy harvesting circuits and antennas for WSNs

Radio frequency (RF) energy harvesting is an emerging technology that will enable to drive the next generation of wireless sensor networks (WSNs) without the need of using batteries. In this paper, we present RF energy harvesting circuits specifically developed for GSM bands (900/1800) and a wearable dual-band antenna suitable for possible implementation within clothes for body worn applications. Besides, we address the development and experimental characterization of three different prototypes of a five-stage Dickson voltage multiplier (with match impedance circuit) responsible for harvesting the RF energy. Different printed circuit board (PCB) fabrication techniques to produce the prototypes result in different values of conversion efficiency. Therefore, we conclude that if the PCB fabrication is achieved by means of a rigorous control in the photo-positive method and chemical bath procedure applied to the PCB it allows for attaining better values for the conversion efficiency. All three prototypes (1, 2 and 3) can power supply the IRIS sensor node for RF received powers of -4 dBm, -6 dBm and -5 dBm, and conversion efficiencies of 20, 32 and 26%, respectively. © 2014 IEEE.

Effect of levodopa on cortico-striatal and cortico-cerebellar circuits in Parkinson's disease

La maladie de Parkinson (MP) est la deuxième maladie neurodégénérative la plus commune. Les symptômes principalement observés chez les patients atteints de la MP sont la rigidité, les tremblements, la bradykinésie et une instabilité posturale. Leur sévérité est souvent asymétrique. La cause principale de ces symptômes moteurs est la dégénérescence du circuit dopaminergique nigro-striatal qui mène à un débalancement d’activité du circuit cortico-striatal. Ce débalancement de circuits est le point essentiel de cette thèse. Dans les protocoles de recherche décrits ici, des patients atteints de la MP (avant et après une dose de levodopa) et des participants contrôles sains ont effectué des mouvements auto-initiés ou en réponse à des stimulis externes pendant que l’on mesurait leur activité cérébrale en imagerie par résonance magnétique fonctionnelle (IRMf). Dans cette thèse, nous abordons et mettons en évidence quatre (4) points principaux. En première partie (chapitre 2), nous présentons un recensement de la littérature sur les cicruits cortico-striataux et cortico-cérébelleux dans la MP. En utilisant des méthodes de neuroimagerie, des changements d’activité cérébrale et cérébelleuse ont été observés chez les patients atteints de la MP comparés aux participants sains. Même si les augmentations d’activité du cervelet ont souvent été attribuées à des mécanismes compensatoires, nos résultats suggèrent qu’elles sont plus probablement liées aux changements pathophysiologiques de la MP et à la perturbation du circuit cortico-cérébelleux. En général, nous suggérons (1) que le circuit cortico-cérébelleux est perturbé chez les patients atteints de la MP, et que les changements d’activité du cervelet sont liés à la pathophysiologie de la MP plutôt qu’à des mécanismes compensatoires. En deuxième partie (chapitre 3), nous discutons des effets de la levodopa sur les hausses et baisses d’activité observés chez les patients atteints de la MP, ainsi que sur l’activité du putamen pendant les mouvements d’origine interne et externe. De nombreuses études en neuroimagerie ont montré une baisse d’activité (hypo-activité) préfrontale liée à la déplétion de dopamine. En revanche, l’utilisation de tâches cognitives a montré des augmentations d’activité (hyper-activité) corticale chez les patients atteints de la MP comparés aux participants sains. Nous avons suggéré précédemment que ces hypo- et hyper-activités des régions préfrontales dépendent de l’implication du striatum. Dans cette thèse nous suggérons de plus (2) que la levodopa ne rétablit pas ces hyper-activations, mais plutôt qu’elles sont liées à la perturbation du circuit méso-cortical, et aussi possiblement associées à l’administration de médication dopaminergique à long terme. Nous montrons aussi (3) que la levodopa a un effet non-spécifique à la tâche sur l’activité du circuit cortico-striatal moteur, et qu’elle n’a pas d’effet sur l’activité du circuit cortico-striatal cognitif. Nous montrons enfin (chapitre 4) que la levodopa a un effet asymétrique sur les mouvements de la main droite et gauche. À peu près 50% des patients atteints de la MP démontrent une asymétrie des symptômes moteurs, et ceci persiste à travers la durée de la maladie. Nos résultats suggèrent (4) que la levodopa pourrait avoir un plus grand effet sur les patrons d’activations des mouvements de la main la plus affectée.

Development and plasticity of locomotor circuits in the zebrafish spinal cord

A fundamental goal in neurobiology is to understand the development and organization of neural circuits that drive behavior. In the embryonic spinal cord, the first motor activity is a slow coiling of the trunk that is sensory-independent and therefore appears to be centrally driven. Embryos later become responsive to sensory stimuli and eventually locomote, behaviors that are shaped by the integration of central patterns and sensory feedback. In this thesis I used a simple vertebrate model, the zebrafish, to investigate in three manners how developing spinal networks control these earliest locomotor behaviors. For the first part of this thesis, I characterized the rapid transition of the spinal cord from a purely electrical circuit to a hybrid network that relies on both chemical and electrical synapses. Using genetics, lesions and pharmacology we identified a transient embryonic behavior preceding swimming, termed double coiling. I used electrophysiology to reveal that spinal motoneurons had glutamate-dependent activity patterns that correlated with double coiling as did a population of descending ipsilateral glutamatergic interneurons that also innervated motoneurons at this time. This work (Knogler et al., Journal of Neuroscience, 2014) suggests that double coiling is a discrete step in the transition of the motor network from an electrically coupled circuit that can only produce simple coils to a spinal network driven by descending chemical neurotransmission that can generate more complex behaviors. In the second part of my thesis, I studied how spinal networks filter sensory information during self-generated movement. In the zebrafish embryo, mechanosensitive sensory neurons fire in response to light touch and excite downstream commissural glutamatergic interneurons to produce a flexion response, but spontaneous coiling does not trigger this reflex. I performed electrophysiological recordings to show that these interneurons received glycinergic inputs during spontaneous fictive coiling that prevented them from firing action potentials. Glycinergic inhibition specifically of these interneurons and not other spinal neurons was due to the expression of a unique glycine receptor subtype that enhanced the inhibitory current. This work (Knogler & Drapeau, Frontiers in Neural Circuits, 2014) suggests that glycinergic signaling onto sensory interneurons acts as a corollary discharge signal for reflex inhibition during movement. v In the final part of my thesis I describe work begun during my masters and completed during my doctoral degree studying how homeostatic plasticity is expressed in vivo at central synapses following chronic changes in network activity. I performed whole-cell recordings from spinal motoneurons to show that excitatory synaptic strength scaled up in response to decreased network activity, in accordance with previous in vitro studies. At the network level, I showed that homeostatic plasticity mechanisms were not necessary to maintain the timing of spinal circuits driving behavior, which appeared to be hardwired in the developing zebrafish. This study (Knogler et al., Journal of Neuroscience, 2010) provided for the first time important in vivo results showing that synaptic patterning is less plastic than synaptic strength during development in the intact animal. In conclusion, the findings presented in this thesis contribute widely to our understanding of the neural circuits underlying simple motor behaviors in the vertebrate spinal cord.

Taming Chaotic Circuits

Control algorithms that exploit chaotic behavior can vastly improve the performance of many practical and useful systems. The program Perfect Moment is built around a collection of such techniques. It autonomously explores a dynamical system's behavior, using rules embodying theorems and definitions from nonlinear dynamics to zero in on interesting and useful parameter ranges and state-space regions. It then constructs a reference trajectory based on that information and causes the system to follow it. This program and its results are illustrated with several examples, among them the phase-locked loop, where sections of chaotic attractors are used to increase the capture range of the circuit.

Alphanumeric LCD infrared control via computer’s parallel port

The present work will explain a method to achieve a remote controlled (via IR LED) alphanumeric Liquid Crystal Display. In modern times, the remote access of different devices has become quite popular, therefore, the aim of this project is to provide a useful tool that will integrate common and easy to access devices. The system includes a C language based user interface, an assembly language code for the AT89C51ED2 microcontroller instructions and some digital electronic circuits needed for the driving and control of both the LCD and the infrared communication, as well as the PC with a parallel port. The interaction of all the devices provides a whole system that can be helpful in different applications, or it can be separated into each one of its different stages to take the best advantage as possible.