Neural Oscillations

Malgré le caractère déterminant des déficits phonologiques pour l’émergence de la dyslexie chez l’enfant, d’autres hypothèses d’explication sont possibles concernant l’origine de ce trouble durable de l’apprentissage de la lecture. La diversité des profils de dyslexie invite à s’intéresser à une variété de déficits visuo-attentionnels susceptibles de participer à des formes de dyslexies dites de surface, mais aussi phonologique ou mixte. Nous proposons d’en préciser la nature, de comprendre leurs retentissements sur la lecture et de fournir des pistes pour les dépasser. Ces déficits attentionnels seront regroupés en trois rubriques : certains perturbent le système d’analyse visuelle précoce spécialisé pour l’orthographe en amont des procédures d’adressage et d’assemblage, d’autres concernent l’orientation spatiale de l’attention, d’autres relèvent enfin de l’attention temporelle. La présentation de travaux sur les liens entre l’attention et les oscillations cérébrales permettra d’évoquer les bases neuronales de mécanismes attentionnels spatio-temporels, fondamentaux pour la dynamique de la lecture et perturbés dans les dyslexies.

Recent years have seen huge advancements in the methods available and used in neuroscience employing EEG or MEG. However, the standard approach is to average a large number of trials for experimentally defined conditions in order to reduce intertrial-variability, i.e. treating it as a source of "noise". Yet it is now more and more accepted that trial-to-trial fluctuations bear functional significance, reflecting fluctuations of "brain states" that predispose perception and action. Such effects are often revealed in a pre-stimulus period, when comparing response variability to an invariant stimulus. However such offline analyses are disadvantageous as they are correlational by drawing conclusions in a posthoc-manner and stimulus presentation is random with respect to the feature of interest. A more direct test is to trigger stimulus presentation when the relevant feature is present. The current paper introduces ConSole (CONstance System for OnLine Eeg), a software...

Oscillatory activity is a widespread phenomenon in nervous systems and has been implicated in numerous functions. Signals that are generated by two separate neuronal sources often demonstrate a consistent phase-relationship in a particular frequency-band, i.e., they demonstrate rhythmic neuronal synchronization. This consistency is conventionally measured by the PLV (phase-locking value) or the spectral coherence measure. Both statistical measures suffer from significant bias, in that their sample estimates overestimate the population statistics for finite sample sizes. This is a significant problem in the neurosciences where statistical comparisons are often made between conditions with a different number of trials or between neurons with a different number of spikes. We introduce a new circular statistic, the PPC (pairwise phase consistency). We demonstrate that the sample estimate of the PPC is a bias-free and consistent estimator of its corresponding population parameter. We show, both analytically and by means of numerical simulations, that the population statistic of the PPC is equivalent to the population statistic of the squared PLV. The variance and mean squared error of the PPC and PLV are compared. Finally, we demonstrate the practical relevance of the method in actual neuronal data recorded from the orbitofrontal cortex of rats that engage in a two-odour discrimination task. We find a strong increase in rhythmic synchronization of spikes relative to the local field potential (as measured by the PPC) for a wide range of low frequencies (including the theta-band) during the anticipation of sucrose delivery in comparison to the anticipation of quinine delivery.

Formulating a minimalist model for language, Gärtner and Sauerland (2007) collected a series of papers exploring the possibility that the recursive gen-erative component plus the conceptual and articulatory interfaces provide the essential components of the system. This was summarized as 'Interfaces + Re-cursion = Language'. Over the past decennium a range of linking hypotheses have been drawn up to better ground this architecture within the brain. In the realms of cognitive and systems neuroscience, the search for the neural code across a number of domains has seen a marked transition from the analysis of individual spike timings to larger patterns of synchronization. This chapter argues that the language sciences should embrace these systems-level developments, with recent findings concerning the scope of possible oscillatory synchronization in the human brain revealing the existence of traveling/migrating oscillations, adding further impetus to reject the typical stasis found in cartographic neurolinguistics models. After exploring empirically-motivated revisions to the neural code for hierarchical phrase structure, it is discussed how this code could provide a new perspective on language disorders, fluid intelligence and language acquisition.

Visual perception is most often studied as a "passive" process in which an observer fixates steadily at point in space so that stimuli can be delivered to the system with spatial precision. Analysis of neuronal signals related to vision is generally keyed to stimulus onset, stimulus movement, etc.; i.e., events external to the observer. In natural "active" vision, however, information is systematically acquired by using eye movements including rapid (saccadic) eye movements, as well as smooth ocular pursuit of moving objects and slower drifts. Here we consider the use of alternating saccades and fixations to gather information from a visual scene. The underlying motor sampling plan contains highly reliable information regarding "where" and "when" the eyes will land, this information can be used predictively to modify firing properties of neurons precisely at the time when this "contextual" information is most useful-when a volley of retinal input enters the system at the onset of each fixation. Analyses focusing on neural events leading to and resulting from shifts in fixation, as well as visual events external to the observer, can provide a more complete and mechanistic understanding of visual information processing. Studies thus far suggest that active vision may be a fundamentally different from that process we usually study with more traditional passive viewing paradigms. In this Perspective we note that active saccadic sampling behavior imposes robust temporal patterning on the activity of neuron ensembles and large-scale neural dynamics throughout the brain's visual pathways whose mechanistic effects on information processing are not yet fully understood. The spatio-temporal sequence of eye movements elicits a succession of temporally predictable quasi-rhythmic sensory inputs, whose encoding is enhanced by entrainment of low frequency oscillations to the rate of eye movements. Review of the pertinent findings underscores the fact that temporal coordination between motor and visual cortices is critical for understanding neural dynamics of active vision and posits that phase entrainment of neuronal oscillations plays a mechanistic role in this process.

In this work, I address the connection of phonetic structure with phonological representations. This classical issue is discussed in the light of recent neurophysiological data which – thanks to direct measurements of temporal and spatial brain activation – provide new avenues to investigate the biological substrate of human language. After describing principal techniques and methods, I critically discuss magnetoencephalographic and electroencephalographic findings of speech processing based on event-related potentials and event-related oscillatory rhythms. The available data do not permit us to clearly disambiguate between neural evidence suggesting pure acoustic patterns and those indicating abstract phonological features. Starting from this evidence, which only at the surface represents a limit, I develop a preliminary proposal where discretization and phonological abstraction are the result of a continuous process that converts spectro-temporal (acoustic) states into neurophysio...

This paper explores the role that "information" may play in a new theory of consciousness.  Through the convergence of physics and neuroscience, I will argue that information is the monistic "common denominator" through which the Cartesian mind-body problem may be resolved.  The paper begins with a speculative quantum mechanical model that potentially provides the information reservoir the philosopher David Chalmers believes a "fundamental theory of consciousness" requires.  The paper next examines the model's underlying assumptions and provides supporting arguments based on Black Hole cosmology and Reversible Computers.  In the following "meditations," the model is restated, first as modes of thought and next in the context of the Hindu Aum (or Om).  Finally, the paper briefly explores the model's implications in our lives, including how prayer and intentionality may alter the probabilities of what occurs in our lives.

Primary scientific literature documents frequency oscillations in both the geosphere and the biosphere arising from a host of different phenomena. At certain frequencies there are known associations between geological oscillations and biological oscillations. This raises the question as to whether these phenomena are functionally related. A compilation of the literature was undertaken, covering a spectral range of 18 orders-of-magnitude extending from 955 Ky/cycle (1.29E-14 Hz) to 0.10 ms/cycle (1.00E+4 Hz), noting those frequencies where there was geological-biological concordance. Concordance was determined for 28 frequency groupings distributed in 10 defined cycle bands within the geological-biological spectrum. The ultradian component of the circadian cycle band was the only band showing little geological-biological concordance, with concordance only at its extreme high-frequency values. Of the 384 references examined reporting geological or biological frequencies, 21 specifically mention concordances between geological and biological oscillations. Further, there are geological and biological frequencies where there are no apparent concordances between the two data sets, indicating that the histogram presented is far from a random distribution. At frequencies where there exists geological and biological concordance, a geological frequency can entrain biological frequencies and provoke a biological response. Lower frequencies affect populations; higher frequencies affect individual organisms. Frequencies of geological-biological concordance provide opportunity for the establishment of multiple interrelated zeitgebers, with disruption of these relationships potentially resulting in physiologic dysfunction, predisposing organisms toward the development of pathology and/or extinction. Précis: Oscillations across eighteen orders-of-magnitude in both the geosphere and the biosphere exhibit concordances where there may be entrainment with resultant geological-biological communication.

In this work, I address the connection of phonetic structure with phonological representations. This classical issue is discussed in the light of recent neurophysiological data which – thanks to direct measurements of temporal and spatial brain activation – provide new avenues to investigate the biological substrate of human language. After describing principal techniques and methods, I critically discuss magnetoencephalographic and electroencephalographic findings of speech processing based on event-related potentials and event-related oscillatory rhythms. The available data do not permit us to clearly disambiguate between neural evidence suggesting pure acoustic patterns and those indicating abstract phonological features. Starting from this evidence, which only at the surface represents a limit, I develop a preliminary proposal where discretization and phonological abstraction are the result of a continuous process that converts spectro-temporal (acoustic) states into neurophysiological states such that some properties of the former undergo changes interacting with the latter until a new equilibrium is reached. I assume that – at the end of the process – phonological segments (and the related categorical processes) take the form of continuous neural states represented by nested cortical oscillatory rhythms spatially distributed in the auditory cortex. Within this perspective, distinctive features (i.e., the relevant representational linguistic primitives) are represented by both spatially local and distributed neural selectivity. I suggest that this hypothesis is suitable to explain hierarchical layout of auditory cortex highly specialized in analyzing different aspects of the speech signal and to explain learning and memory processes during the acquisition of phonological systems.

Perception, cognition, and social interaction depend upon coordinated neural activity. This coordination operates within noisy, overlapping, and distributed neural networks operating at multiple timescales. These networks are built upon a structural scaffolding with intrinsic neuroplasticity that changes with development, aging, disease, and personal experience. In this paper we begin from the perspective that successful interregional communication relies upon the transient synchronization between distinct low frequency (<80 Hz) oscillations, allowing for brief windows of communication via phase-coordinated local neuronal spiking. From this, we construct a theoretical framework for dynamic network communication, arguing that these networks reflect a balance between oscillatory coupling and local population spiking activity, and that these two levels of activity interact. We theorize that when oscillatory coupling is too strong, spike timing within the local neuronal population becomes too synchronous; when oscillatory coupling is too weak, spike timing is too disorganized. Each results in specific disruptions to neural communication. These alterations in communication dynamics may underlie cognitive changes associated with healthy development and aging, in addition to neurological and psychiatric disorders. A number of neurological and psychiatric disorders— including Parkinson’s disease, autism, depression, schizophrenia, and anxiety—are associated with abnormalities in oscillatory activity. Although aging, psychiatric and neurological disease, and experience differ in the biological changes to structural grey or white matter, neurotransmission, and gene expression, our framework suggests that any resultant cognitive and behavioral changes in normal or disordered states, or their treatment, is a product of how these physical processes affect dynamic network communication.

We explore the potential that brain oscillations have for improving our understanding of how language develops, is processed in the brain, and initially evolved in our species. The different synchronization patterns of brain rhythms can account for different perceptual and cognitive functions, and we argue that this includes language. We aim to address six distinct questions-the What, How, Where, Who, Why, and When questions-pertaining to oscillatory investigations of language. Language deficits found in clinical conditions like autism, schizophrenia and dyslexia can be satisfactorily construed in terms of an abnormal, disorder-specific pattern of brain rhythmicity. Lastly, an eco-evo-devo approach to language is defended with explicit reference to brain oscillations, embracing a framework that considers language evolution to be the result of a changing environment surrounding developmental paths of the primate brain.

Objectives: Magnetic resonance imaging (MRI) studies showed that grey matter integrity is an important determinant of slow waves (SW) properties in young subjects. During aging, SWs become scarce and their amplitude decreases mostly in frontal regions, where cortical thinning is also predominant. We sought to assess the role of cortical thinning in age-related changes in SW properties.
Methods: Polysomnography was recorded in 30 young(20-30 y/o; 16 men) and 33 middle-aged(50-70 y/o; 15 men) subjects. Mean SW density and amplitude between pairs of frontal electrodes (F3-F4) was calculated for all-night non-rapid-eye-movement sleep. Subjects underwent a brain MRI, and cortical thickness (CT) was calculated. Mediation analyses were performed to investigate the role of cortical thinning in the age-related changes in SW.
Results: Compared to the young, middle-aged subjects showed lower SW density and amplitude (p< 0.05). Controlling for the effects of age, SW density was associated with CT in fronto-temporal gyri, while SW amplitude was associated with CT in fronto-parieto-occipital gyri (p< 0.05-corrected). Mediation analyses and effect size measures showed that thinning of the precentral and infero-temporal gyri explained a large proportion of the age-effect on SW density(K2: 0.44), while thinning of the precuneus explained a small proportion of the age-effect on SW amplitude(K2:0.22).
Conclusions: Our results shows that thinning of specific cortical regions are involved in SW changes during adulthood. Since these regions are involved in SW generation and propagation, future studies should assess how cortical and subcortical connectivity influences SW propagation during aging.

During sleep, neocortical neuronal networks oscillate slowly (<1 Hz) between periods of activity (UP states) and silence (DOWN states). UP states favor the interaction between thalamic-generated spindles (7-14 Hz) and cortically generated gamma (30-80 Hz) waves. We studied how these three nested oscillations modulate fast-spiking interneuron (FSi) activity in vivo in VGAT-Venus transgenic rats. Our data describe a population of FSi that discharge "early" within UP states and another population that discharge "late." Early FSi tended to be silent during epochs of desynchronization, whereas late FSi were active. We hypothesize that late FSi may be responsible for generating the gamma oscillations associated with cognitive processing during wakefulness. Remarkably, FSi populations were differently modulated by spindle and gamma rhythms. Early FSi were robustly coupled to spindles and always discharged earlier than late FSi within spindle and gamma cycles. The preferred firing phase during spindle and gamma waves was strongly correlated in each cell, suggesting a cross-frequency coupling between oscillations. Our results suggest a precise spatiotemporal pattern of FSi activity during UP states, whereby information rapidly flows between early and late cells, initially promoted by spindles and efficiently extended by local gamma oscillations.

This paper situates an original model of reentrant oscillatory multiplexing within the philosophy of time consciousness to argue for an extensionalist theory of the specious present. I develop a detailed differential latency model of apparent motion to show how the ordinality of experiential content is isomorphic to the ordinality of relevant brain processes. I argue that the theory presented has resources to account for other key features of the specious present, including the representational discreteness between successive conscious moments as well as the phenomen-ological continuity between them. This work not only shows the plausibility of an extensionalist philosophical theory, it also illustrates the utility of differential latency views in squaring temporal illusions with empirically supported neurodynamics.

For the past two decades, it has widely been assumed by linguists that there is a single computational operation, Merge, which is unique to language, distinguishing it from other cognitive domains. The intention of this paper is to progress the discussion of language evolution in two ways: (i) survey what the ethological record reveals about the uniqueness of the human computational system, and (ii) explore how syntactic theories account for what ethology may determine to be human-specific. It is shown that the operation Label, not Merge, constitutes the evolutionary novelty which distinguishes human language from non-human computational systems; a proposal lending weight to a Weak Continuity Hypothesis and leading to the formation of what is termed Computational Ethology. Some directions for future ethological research are suggested.

Recent years have seen an explosion of interest in using neural oscillations to characterize the mechanisms supporting cognition and emotion. Oftentimes, oscillatory activity is indexed by mean power density in predefined frequency bands. Some investigators use broad bands originally defined by prominent surface features of the spectrum. Others rely on narrower bands originally defined by spectral factor analysis (SFA). Presently, the robustness and sensitivity of these competing band definitions remains unclear. Here, a Monte Carlo-based SFA strategy was used to decompose the tonic (“resting” or “spontaneous”) electroencephalogram (EEG) into five bands: delta (1–5 Hz), alpha-low (6–9 Hz), alpha-high (10–11 Hz), beta (12–19 Hz), and gamma (N21 Hz). This pattern was consistent across SFA methods, artifact correction/rejection procedures, scalp regions, and samples. Subsequent analyses revealed that SFA failed to deliver enhanced sensitivity; narrow alpha sub-bands proved no more sensitive than the classical broadband to individual differences in temperament or mean differences in task-induced activation. Other analyses suggested that residual ocular and muscular artifact was the dominant source of activity during quiescence in the delta and gamma bands. This was observed following threshold-based artifact rejection or independent component analysis (ICA)- based artifact correction, indicating that such procedures do not necessarily confer adequate protection. Collectively, these findings highlight the limitations of several commonly used EEG procedures and underscore the necessity of routinely performing exploratory data analyses, particularly data visualization, prior to hypothesis testing. They also suggest the potential benefits of using techniques other than SFA for interrogating high-dimensional EEG datasets in the frequency or time–frequency (event-related spectral perturbation, event-related synchronization/desynchronization) domains. KEY WORDS: principal components analysis (PCA); exploratory factor analysis (EFA); blind source separation (BSS); resting neural activity; resting EEG; frontal alpha asymmetry; frontal EEG asymmetry.

Our understanding of human visual perception generally rests on the assumption that conscious visual states represent the interaction of spatial structures in the environment and our nervous system. This assumption is questioned by circumstances where conscious visual states can be triggered by external stimulation which is not primarily spatially defined. Here, subjective colors and forms are evoked by flickering light while the precise nature of those experiences varies over flicker frequency and phase. What’s more, the occurrence of one subjective experience appears to be associated with the occurrence of others. While these data indicate that conscious visual experience may be evoked directly by particular variations in the flow of spatially unstructured light over time it must be assumed that the systems responsible are essentially temporal in character and capable of representing a variety of visual forms and colors, coded in different frequencies or at different phases of the same processing rhythm.

Objectives
The purpose of this theoretical analysis of current research on ADHD is to provide an account integrating executive functional profiles with its broader structural neurodevelopmental profile.

Methods
Comparative theoretical analyses between executive functional deficit disorder models of ADHD and results from default mode network fMRI data. This was followed by an analysis of the temporal profile of ADHD and phase synchronous neural assemblies.

Results
Comparative analyses suggest disparities within executive functional deficit disorder models and discontinuities between executive functional and structural profiles of ADHD. Analysis of the temporal signature of ADHD provides a potential avenue for integrating different profiles by means of anchoring executive functions within inherent diachronic neurocognitive organization.

Conclusions
The analyses provided suggest that executive functional deficits in ADHD arise from much broader idiosyncrasies, rooted within the inherent diachronic organization of neurocognitive function, and whose challenges must be understood in conjunction with socio cultural environmental factors.

Executive functions and working memory are long known to involve the prefrontal cortex (PFC), and two PFC-projecting areas: midline/paramidline thalamus (MLT) and cornus ammonis 1 (CA1)/subiculum of the hippocampal formation (HF). An increasing number of rodent electrophysiology studies are examining these substrates together, thus providing circuit-level perspectives on input convergence, synaptic plasticity and functional coupling, as well as insights into cognition mechanisms and brain disorders. Our review article puts this literature into a method-oriented narrative. As revisited throughout the text, limbic thalamic and hippocampal afferents to the PFC gate one another's inputs, which in turn are modulated by PFC interneurons and ascending monoaminergic projections. In addition, long-term synaptic plasticity, paired-pulse facilitation (PPF), and event-related potentials (ERP) dynamically vary across PFC-related circuits during learning paradigms and drug effects. Finally, thalamic-prefrontal loops, which have been shown to amplify both cognitive processes and limbic seizures, are also being implicated as relays in the prefrontal-hippocampal feedback, contributing to spatial navigation and decision making. Based on these issues, we conclude the review with a critical synthesis and some research directions.

The olivo-cerebellar system has been implicated in temporal coordination of task components. Here, we propose a novel model that enables the olivo-cerebellar system to function as a generator of temporal patterns. These patterns could be used for timing of motor, sensory and cognitive tasks. The proposed mechanism for the generation of these patterns is based on subthreshold oscillations in a network of inferior olivary neurons and their control by the cerebellar cortex and nuclei. Our model, which integrates a large body of anatomical and physiological observations, lends itself to simple, testable predictions and provides a new conceptual framework for olivo-cerebellar research.

Catching a thrown ball requires a tight coupling between perception and motor control. In this review, we examine multidimensional information processing across various perceptual and motor tasks. We summarize how perception, timing and action can be understood in terms of the coupling of gamma band oscillations, which represent the local activities of brain circuits, to a specific phase of long-range low-frequency oscillations. We propose a temporal window of integration that emerges from cross-frequency coupling that serves to produce optimized action.

The brain is an orchestra playing a harmonious symphony of the Mind that we experience as the unity of our picture of the world and ourselves in this world. Violations of this process, which we call mental pathologies, lead to dissonances and even complete disintegration of the picture.
How do billions of neurons perform this symphony? In other words, how does the brain create a coherent and integral model of reality while maintaining the identity of each encoded signal? In neuroscience, this question is called the binding problem.
The harmony of the Mind is a physical phenomenon, and it must be explained physically. The author solves this riddle, based on the Theory of Energy Harmony and the Teleological Transduction Theory developed in the previous volumes of the series. The book describes the physical binding mechanism that makes the symphony of the Mind harmonious and reveals the subtle nuances of its physiological implementation in the brain.

The pathogenesis of fibromyalgia is still unknown. Core symptoms include pain, depression and sleep disturbances with high comorbidity, suggesting alterations in the monoaminergic system as a common origin of this disease. The reserpine-induced myalgia model (RIM) lowers pain thresholds and produces depressive-like symptoms. The present work aims to evaluate temporal dynamics in the oscillatory profiles and motor activity during sleep in this model and to evaluate if the model mimics the sleep disorders that occur in fibromyalgia patients. Hippocampal and EMG activity were recorded in chronically implanted rats. Following 3 days of basal recordings, reserpine was administered on 3 consecutive days to achieve the RIM. Post-reserpine recordings were taken on alternate days for 21 days. Reserpine induced changes in the sleep architecture with more transitions between states, and a different pattern between the administration period and post-reserpine weeks. Administration days were characterized by a larger amount of REM sleep with dominant theta waves without atonia. Following the reserpinization, theta oscillations were always more fragmented and with lower frequency. On the post-reserpine days, sleep was dominated by slow-wave sleep with fast intrusions and reduced hierarchical coupling with spindles and ripples. Simultaneous electromyography recordings also showed muscle twitches during sleep and the dissociation of theta activity and muscle atonia. Abnormally high slow waves, alpha/delta intrusions, frequent transitions and muscle twitches are common traits in fibromyalgia. Therefore, our analyses support the validity of the reserpine-induced myalgia model to study sleep disorders in fibromyalgia, and provide new insights into the research of oscillographic biomarkers. This article is protected by copyright. All rights reserved.

My intention in this piece is to briefly outline a novel hypothesis regarding the neurobiological implementation of feature-set binding, the labeling of feature-sets, and the resolution of linguistic dependencies arising from the cyclic combination of these labeled objects. One of the numerous motivations for this was reading Robert C. Berwick & Noam Chomsky's (B&C) recent book Why Only Us: Language and Evolution (Berwick & Chomsky 2016; henceforth WOU), which struck me as moderately comprehensive in its interdisciplinary scope (including good critical commentary on recent work in comparative neuroprimatology and theoretical biology) but severely impoverished in its range of linking hypotheses between these disciplines.

— The problem of emergent synchronization patterns in a complex network of coupled oscillators has caught scientists' interest in a lot of different disciplines. In particular, from a biological point of view, considerable attention has been recently devoted to the study of the human brain as a network of different cortical regions that show coherent activity during resting-state. In literature, there can be found different large-scale models of resting-state dynamics in health and disease. In this context, the Kuramoto model, a classical model apt to describe oscillators' dynamics, has been extended to capture the spatial displacement and the communication conditions in such brain network. Starting from a previous work in this field [1], we analyze this modified model and compare it with other existing large-scale models. In doing so, our aim is to promote a set of mathematical tools useful to better understand real experimental data in neuroscience and estimate brain dynamics.

Prior expectations have a powerful influence on perception, biasing both decision and confidence. However, how this occurs at the neural level remains unclear. It has been suggested that spontaneous alpha-band neural oscillations represent rhythms of the perceptual system that periodically modulate perceptual judgements. We hypothesised that these oscillations instantiate the effects of expectations. While collecting scalp EEG, participants performed a detection task that orthogonally manipulated perceptual expectations and attention. Trial-by-trial retrospective confidence judgements were also collected. Results showed that independently of attention, pre-stimulus occipital alpha phase predicted the weighting of expectations on yes/no decisions. Moreover, phase predicted the influence of expectations on confidence. Thus, expectations periodically bias objective and subjective perceptual decision-making together, prior to stimulus onset. Our results suggest that alpha-band neural oscillations periodically transmit prior evidence to visual cortex, changing the baseline from which evidence accumulation begins. In turn, our results inform accounts of how expectations shape early visual processing.

The wide range of shape variations for handwritten digits requires an adequate representation of thediscriminating features for classification. For the recognition of characters or numerals requires pixel valuesof a normalized raster image and proper features to reach very good classification rate. This paper primarily concerns the problem of isolated handwritten numeral recognition of English scripts.Multilayer Perceptron(MLP) classifier is used for classification. The principalcontributions presented here are preprocessing, feature extraction and multilayer perceptron (MLP) classifiers.The strength of our approach is efficient feature extraction and the comprehensive classification scheme due to which, we have been able to achieve a recognition rate of 95.6, better than the previous approaches.

"Models of wavelets for estimating MRI-oscillations from evoked and spontaneous EEG/MEG activity"

-Society for Neuroscience Meeting Abstract. On line sfn.org

Juan Fernando Gomez-Molina, David A Pineda, Molina-R Lylliam

ABSTRACT:
Location: South Hall A - Presentation Time: Tuesday, Oct 20, 2009, 4:00 PM - 5:00 PM -

Authors:
*J. F. GOMEZ-MOLINA 1,
D. A. PINEDA 2,
L. MOLINA-R 3;

- 1 Int Group of Neuro Cra 64c #48-94 Suramericana 3 (603) Medellin Colombia, Medellin, Colombia;
- 2 Grupo de Neuropsicologia y Conducta, Fac. of Psychology, Univ. of San Buenaventura, Medellin, Colombia;
- 3 Int Group Neuro Cra 64c # 48 - 94 (603), Medellin, Colombia.

      - Introduction.

    Wavelets are small waves that decay quickly (their envelope decreases fast). They generate signals with self-similar characteristics like the EEG and the fMRI. On the other hand, it was suggested that a visual stimulus desynchronize -or spatially fragment- alpha rhythms (Gomez, SfN 2008). Slow (<0.1Hz), resting fMRI-BOLD signals might display similar fragmentation (alpha power and BOLD seem to be related).

    - Methods.

      We convert synthetic EEG/MEG signals into fMRI (see table): 
    (i) Using gamma and hemodynamic response functions.

    (ii) Using wavelets and Gabor functions.
 
    The model can be used with real-EEG evoked potentials (i.e. normals vs. children with ADHD).

    - Conclusions.

      Wavelets can express more explicitly the intrinsic, spontaneous oscillations(*) of the EEG/fMRI and the stimulus-induced changes. They imply the existence of peaks in fMRI responses (resonances) at certain stimulus frequencies.

    Wavelets can model evoked signals as waves in sensory pathways which might form BOLD-related functional connections.

    Diffusion-fMRI-response (ahead from BOLD onset and offset in visual cortex) can be estimated from it and a fast component -icMRI (**), caused by the effects of the ionic currents on water protons and MRI-times (TE, T1)- can be extracted from slower cell-swelling signals.

    - (*) Llinas R. I of the vortex. MIT Press.

    - (**) Gomez-M Juan F (2008) Combination of Visual Stimulation and EEG with fMRI/"Ionic-current-MRI Dyn Neuro XVI, NIMH.

    Society for Neuroscience Meeting - Chicago IL, USA -, South Hall A Chicago IL USA; 10/2009  On line sfn.org

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