The Island of Drive. Representations, somatic states and the origin of drive

Freud defined the drive as "a concept on the frontier between the mental and the somatic". Today this view that was based on clinical observations interpreted within the psychoanalytical framework, can be revisited in light of the current neuroscientific notions of neuronal plasticity and somatic states. Indeed, through the mechanisms of plasticity experience leaves a trace that forms the neural basis of a representation of the experience. Such a representation R is associated with a somatic state S in the sense taken from the "somatic marker" model of Damasio. Thus, the internal reality of the subject, particularly the unconscious one, is constituted by such connected R's and S's. In the model that we discuss, the posterior insula represents the primary interoceptive cortex where information about somatic states S converges, while in the anterior insula the connection between R and S can take place and establish a neurobiological correlate for the notion of drive. We posit that the re-representations of S associated with R in the anterior insula may correspond to the Vorstellungsrepräsentanz postulated by Freud. We further propose that the tension between R and S established in the anterior insula is discharged according to the notion of drive through the motor arm of the limbic system, namely the anterior cingulate cortex which is heavily connected with the anterior insula.

Organization and plasticity of auditory spatial representations

Spatial hearing refers to a set of abilities enabling us to determine the location of sound sources, redirect our attention toward relevant acoustic events, and recognize separate sound sources in noisy environments. Determining the location of sound sources plays a key role in the way in which humans perceive and interact with their environment. Deficits in sound localization abilities are observed after lesions to the neural tissues supporting these functions and can result in serious handicaps in everyday life. These deficits can, however, be remediated (at least to a certain degree) by the surprising capacity of reorganization that the human brain possesses following damage and/or learning, namely, the brain plasticity. In this thesis, our aim was to investigate the functional organization of auditory spatial functions and the learning-induced plasticity of these functions. Overall, we describe the results of three studies. The first study entitled "The role of the right parietal cortex in sound localization: A chronometric single pulse transcranial magnetic stimulation study" (At et al., 2011), study A, investigated the role of the right parietal cortex in spatial functions and its chronometry (i.e. the critical time window of its contribution to sound localizations). We concentrated on the behavioral changes produced by the temporarily inactivation of the parietal cortex with transcranial magnetic stimulation (TMS). We found that the integrity of the right parietal cortex is crucial for localizing sounds in the space and determined a critical time window of its involvement, suggesting a right parietal dominance for auditory spatial discrimination in both hemispaces. In "Distributed coding of the auditory space in man: evidence from training-induced plasticity" (At et al., 2013a), study B, we investigated the neurophysiological correlates and changes of the different sub-parties of the right auditory hemispace induced by a multi-day auditory spatial training in healthy subjects with electroencephalography (EEG). We report a distributed coding for sound locations over numerous auditory regions, particular auditory areas code specifically for precise parts of the auditory space, and this specificity for a distinct region is enhanced with training. In the third study "Training-induced changes in auditory spatial mismatch negativity" (At et al., 2013b), study C, we investigated the pre-attentive neurophysiological changes induced with a training over 4 days in healthy subjects with a passive mismatch negativity (MMN) paradigm. We showed that training changed the mechanisms for the relative representation of sound positions and not the specific lateralization themselves and that it changed the coding in right parahippocampal regions. - L'audition spatiale désigne notre capacité à localiser des sources sonores dans l'espace, de diriger notre attention vers les événements acoustiques pertinents et de reconnaître des sources sonores appartenant à des objets distincts dans un environnement bruyant. La localisation des sources sonores joue un rôle important dans la façon dont les humains perçoivent et interagissent avec leur environnement. Des déficits dans la localisation de sons sont souvent observés quand les réseaux neuronaux impliqués dans cette fonction sont endommagés. Ces déficits peuvent handicaper sévèrement les patients dans leur vie de tous les jours. Cependant, ces déficits peuvent (au moins à un certain degré) être réhabilités grâce à la plasticité cérébrale, la capacité du cerveau humain à se réorganiser après des lésions ou un apprentissage. L'objectif de cette thèse était d'étudier l'organisation fonctionnelle de l'audition spatiale et la plasticité induite par l'apprentissage de ces fonctions. Dans la première étude intitulé « The role of the right parietal cortex in sound localization : A chronometric single pulse study » (At et al., 2011), étude A, nous avons examiné le rôle du cortex pariétal droit dans l'audition spatiale et sa chronométrie, c'est-à- dire le moment critique de son intervention dans la localisation de sons. Nous nous sommes concentrés sur les changements comportementaux induits par l'inactivation temporaire du cortex pariétal droit par le biais de la Stimulation Transcrânienne Magnétique (TMS). Nous avons démontré que l'intégrité du cortex pariétal droit est cruciale pour localiser des sons dans l'espace. Nous avons aussi défini le moment critique de l'intervention de cette structure. Dans « Distributed coding of the auditory space : evidence from training-induced plasticity » (At et al., 2013a), étude B, nous avons examiné la plasticité cérébrale induite par un entraînement des capacités de discrimination auditive spatiale de plusieurs jours. Nous avons montré que le codage des positions spatiales est distribué dans de nombreuses régions auditives, que des aires auditives spécifiques codent pour des parties données de l'espace et que cette spécificité pour des régions distinctes est augmentée par l'entraînement. Dans « Training-induced changes in auditory spatial mismatch negativity » (At et al., 2013b), étude C, nous avons examiné les changements neurophysiologiques pré- attentionnels induits par un entraînement de quatre jours. Nous avons montré que l'entraînement modifie la représentation des positions spatiales entraînées et non-entrainées, et que le codage de ces positions est modifié dans des régions parahippocampales.

Neural plasticity associated with recently versus often heard objects.

In natural settings the same sound source is often heard repeatedly, with variations in spectro-temporal and spatial characteristics. We investigated how such repetitions influence sound representations and in particular how auditory cortices keep track of recently vs. often heard objects. A set of 40 environmental sounds was presented twice, i.e. as prime and as repeat, while subjects categorized the corresponding sound sources as living vs. non-living. Electrical neuroimaging analyses were applied to auditory evoked potentials (AEPs) comparing primes vs. repeats (effect of presentation) and the four experimental sections. Dynamic analysis of distributed source estimations revealed i) a significant main effect of presentation within the left temporal convexity at 164-215ms post-stimulus onset; and ii) a significant main effect of section in the right temporo-parietal junction at 166-213ms. A 3-way repeated measures ANOVA (hemisphere×presentation×section) applied to neural activity of the above clusters during the common time window confirmed the specificity of the left hemisphere for the effect of presentation, but not that of the right hemisphere for the effect of section. In conclusion, spatio-temporal dynamics of neural activity encode the temporal history of exposure to sound objects. Rapidly occurring plastic changes within the semantic representations of the left hemisphere keep track of objects heard a few seconds before, independent of the more general sound exposure history. Progressively occurring and more long-lasting plastic changes occurring predominantly within right hemispheric networks, which are known to code for perceptual, semantic and spatial aspects of sound objects, keep track of multiple exposures.

Neural correlates of affordance competition in dorsal premotor cortex

Le travail présenté dans cette thèse porte sur le rôle du cortex prémoteur dorsal (PMd) au sujet de la prise de décision (sélection d’une action parmis nombreux choix) et l'orientation visuelle des mouvements du bras. L’ouvrage décrit des expériences électrophysiologiques chez le singe éveillé (Macaca mulatta) permettant d’adresser une fraction importante des prédictions proposées par l'hypothèse des affordances concurrentes (Cisek, 2006; Cisek, 2007a). Cette hypothèse suggère que le choix de toute action est l’issue d'une concurrence entre les représentations internes des exigences et des atouts de chacune des options présentées (affordances; Gibson, 1979). Un intérêt particulier est donné au traitement de l'information spatiale et la valeur des options (expected value, EV) dans la prise de décisions. La première étude (article 1) explore la façon dont PMd reflète ces deux paramètres dans la période délai ainsi que de leur intéraction. La deuxième étude (article 2) explore le mécanisme de décision de façon plus détaillée et étend les résultats au cortex prémoteur ventral (PMv). Cette étude porte également sur la représentation spatiale et l’EV dans une perspective d'apprentissage. Dans un environnement nouveau les paramètres spatiaux des actions semblent être présents en tout temps dans PMd, malgré que la représentation de l’EV apparaît uniquement lorsque les animaux commencent à prendre des décisions éclairées au sujet de la valeur des options disponibles. La troisième étude (article 3) explore la façon dont PMd est impliqué aux “changements d'esprit“ dans un procès de décision. Cette étude décrit comment la sélection d’une action est mise à jour à la suite d'une instruction de mouvement (GO signal). I II Les résultats principaux des études sont reproduits par un modèle computationnel (Cisek, 2006) suggérant que la prise de décision entre plusieurs actions alternatives peux se faire par voie d’un mécanisme de concurrence (biased competition) qui aurait lieu dans la même région qui spécifie les actions.

Deep learning of representations and its application to computer vision

L’objectif de cette thèse par articles est de présenter modestement quelques étapes du parcours qui mènera (on espère) à une solution générale du problème de l’intelligence artificielle. Cette thèse contient quatre articles qui présentent chacun une différente nouvelle méthode d’inférence perceptive en utilisant l’apprentissage machine et, plus particulièrement, les réseaux neuronaux profonds. Chacun de ces documents met en évidence l’utilité de sa méthode proposée dans le cadre d’une tâche de vision par ordinateur. Ces méthodes sont applicables dans un contexte plus général, et dans certains cas elles on tété appliquées ailleurs, mais ceci ne sera pas abordé dans le contexte de cette de thèse. Dans le premier article, nous présentons deux nouveaux algorithmes d’inférence variationelle pour le modèle génératif d’images appelé codage parcimonieux “spike- and-slab” (CPSS). Ces méthodes d’inférence plus rapides nous permettent d’utiliser des modèles CPSS de tailles beaucoup plus grandes qu’auparavant. Nous démontrons qu’elles sont meilleures pour extraire des détecteur de caractéristiques quand très peu d’exemples étiquetés sont disponibles pour l’entraînement. Partant d’un modèle CPSS, nous construisons ensuite une architecture profonde, la machine de Boltzmann profonde partiellement dirigée (MBP-PD). Ce modèle a été conçu de manière à simplifier d’entraînement des machines de Boltzmann profondes qui nécessitent normalement une phase de pré-entraînement glouton pour chaque couche. Ce problème est réglé dans une certaine mesure, mais le coût d’inférence dans le nouveau modèle est relativement trop élevé pour permettre de l’utiliser de manière pratique. Dans le deuxième article, nous revenons au problème d’entraînement joint de machines de Boltzmann profondes. Cette fois, au lieu de changer de famille de modèles, nous introduisons un nouveau critère d’entraînement qui donne naissance aux machines de Boltzmann profondes à multiples prédictions (MBP-MP). Les MBP-MP sont entraînables en une seule étape et ont un meilleur taux de succès en classification que les MBP classiques. Elles s’entraînent aussi avec des méthodes variationelles standard au lieu de nécessiter un classificateur discriminant pour obtenir un bon taux de succès en classification. Par contre, un des inconvénients de tels modèles est leur incapacité de générer deséchantillons, mais ceci n’est pas trop grave puisque la performance de classification des machines de Boltzmann profondes n’est plus une priorité étant donné les dernières avancées en apprentissage supervisé. Malgré cela, les MBP-MP demeurent intéressantes parce qu’elles sont capable d’accomplir certaines tâches que des modèles purement supervisés ne peuvent pas faire, telles que celle de classifier des données incomplètes ou encore celle de combler intelligemment l’information manquante dans ces données incomplètes. Le travail présenté dans cette thèse s’est déroulé au milieu d’une période de transformations importantes du domaine de l’apprentissage à réseaux neuronaux profonds qui a été déclenchée par la découverte de l’algorithme de “dropout” par Geoffrey Hinton. Dropout rend possible un entraînement purement supervisé d’architectures de propagation unidirectionnel sans être exposé au danger de sur- entraînement. Le troisième article présenté dans cette thèse introduit une nouvelle fonction d’activation spécialement con ̧cue pour aller avec l’algorithme de Dropout. Cette fonction d’activation, appelée maxout, permet l’utilisation de aggrégation multi-canal dans un contexte d’apprentissage purement supervisé. Nous démontrons comment plusieurs tâches de reconnaissance d’objets sont mieux accomplies par l’utilisation de maxout. Pour terminer, sont présentons un vrai cas d’utilisation dans l’industrie pour la transcription d’adresses de maisons à plusieurs chiffres. En combinant maxout avec une nouvelle sorte de couche de sortie pour des réseaux neuronaux de convolution, nous démontrons qu’il est possible d’atteindre un taux de succès comparable à celui des humains sur un ensemble de données coriace constitué de photos prises par les voitures de Google. Ce système a été déployé avec succès chez Google pour lire environ cent million d’adresses de maisons.

Atypical neural self-representation in autism

The 'self' is a complex multidimensional construct deeply embedded and in many ways defined by our relations with the social world. Individuals with autism are impaired in both self-referential and other-referential social cognitive processing. Atypical neural representation of the self may be a key to understanding the nature of such impairments. Using functional magnetic resonance imaging we scanned adult males with an autism spectrum condition and age and IQ-matched neurotypical males while they made reflective mentalizing or physical judgements about themselves or the British Queen. Neurotypical individuals preferentially recruit the middle cingulate cortex and ventromedial prefrontal cortex in response to self compared with other-referential processing. In autism, ventromedial prefrontal cortex responded equally to self and other, while middle cingulate cortex responded more to other-mentalizing than self-mentalizing. These atypical responses occur only in areas where self-information is preferentially processed and does not affect areas that preferentially respond to other-referential information. In autism, atypical neural self-representation was also apparent via reduced functional connectivity between ventromedial prefrontal cortex and areas associated with lower level embodied representations, such as ventral premotor and somatosensory cortex. Furthermore, the magnitude of neural self-other distinction in ventromedial prefrontal cortex was strongly related to the magnitude of early childhood social impairments in autism. Individuals whose ventromedial prefrontal cortex made the largest distinction between mentalizing about self and other were least socially impaired in early childhood, while those whose ventromedial prefrontal cortex made little to no distinction between mentalizing about self and other were the most socially impaired in early childhood. These observations reveal that the atypical organization of neural circuitry preferentially coding for self-information is a key mechanism at the heart of both self-referential and social impairments in autism.

Complex-valued b-spline neural networks for modelling and inverse of wiener systems

Communication signal processing applications often involve complex-valued (CV) functional representations for signals and systems. CV artificial neural networks have been studied theoretically and applied widely in nonlinear signal and data processing [1–11]. Note that most artificial neural networks cannot be automatically extended from the real-valued (RV) domain to the CV domain because the resulting model would in general violate Cauchy-Riemann conditions, and this means that the training algorithms become unusable. A number of analytic functions were introduced for the fully CV multilayer perceptrons (MLP) [4]. A fully CV radial basis function (RBF) nework was introduced in [8] for regression and classification applications. Alternatively, the problem can be avoided by using two RV artificial neural networks, one processing the real part and the other processing the imaginary part of the CV signal/system. A even more challenging problem is the inverse of a CV

Enhanced affective brain representations of chocolate in cravers vs. non-cravers

To examine the neural circuitry involved in food craving, in making food particularly appetitive and thus in driving wanting and eating, we used fMRI to measure the response to the flavour of chocolate, the sight of chocolate and their combination in cravers vs. non-cravers. Statistical parametric mapping (SPM) analyses showed that the sight of chocolate produced more activation in chocolate cravers than non-cravers in the medial orbitofrontal cortex and ventral striatum. For cravers vs. non-cravers, a combination of a picture of chocolate with chocolate in the mouth produced a greater effect than the sum of the components (i.e. supralinearity) in the medial orbitofrontal cortex and pregenual cingulate cortex. Furthermore, the pleasantness ratings of the chocolate and chocolate-related stimuli had higher positive correlations with the fMRI blood oxygenation level-dependent signals in the pregenual cingulate cortex and medial orbitofrontal cortex in the cravers than in the non-cravers. To our knowledge, this is the first study to show that there are differences between cravers and non-cravers in their responses to the sensory components of a craved food in the orbitofrontal cortex, ventral striatum and pregenual cingulate cortex, and that in some of these regions the differences are related to the subjective pleasantness of the craved foods. Understanding individual differences in brain responses to very pleasant foods helps in the understanding of the mechanisms that drive the liking for specific foods and thus intake of those foods.

Análise da incerteza na representação de classes de cobertura do solo urbano resultantes da aplicação de uma rede neural artificial

The great diversity of materials that characterizes the urban environment determines a structure of mixed classes in a classification of multiespectral images. In that sense, it is important to define an appropriate classification system using a non parametric classifier, that allows incorporating non spectral (such as texture) data to the process. They also allow analyzing the uncertainty associated to each class from the output alues of the network calculated in relation to each class. Considering these properties, an experiment was carried out. This experiment consisted in the application of an Artificial Neural Network aiming at the classification of the urban land cover of Presidente Prudente and the analysis of the uncertainty in the representation of the mapped thematic classes. The results showed that it is possible to discriminate the variations in the urban land cover through the application of an Artificial Neural Network. It was also possible to visualize the spatial variation of the uncertainty in the attribution of classes of urban land cover from the generated representations. The class characterized by a defined pattern as intermediary related to the impermeability of the urban soil presented larger ambiguity degree and, therefore, larger mixture.

Análise da incerteza na representação de classes temáticas resultantes da aplicação de uma rede neural artificial

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Plasticity in body and peripersonal space representations

A successful interaction with objects in the environment requires integrating information concerning object-location with the shape, dimension and position of body parts in space. The former information is coded in a multisensory representation of the space around the body, i.e. peripersonal space (PPS), whereas the latter is enabled by an online, constantly updated, action-orientated multisensory representation of the body (BR) that is critical for action. One of the critical features of these representations is that both PPS and BR are not fixed, but they dynamically change depending on different types of experience. In a series of experiment, I studied plastic properties of PPS and BR in humans. I have developed a series of methods to measure the boundaries of PPS representation (Chapter 4), to study its neural correlates (Chapter 3) and to assess BRs. These tasks have been used to study changes in PPS and BR following tool-use (Chapter 5), multisensory stimulation (Chapter 6), amputation and prosthesis implantation (Chapter 7) or social interaction (Chapter 8). I found that changes in the function (tool-use) and the structure (amputation and prosthesis implantation) of the physical body elongate or shrink both PPS and BR. Social context and social interaction also shape PPS representation. Such high degree of plasticity suggests that our sense of body in space is not given at once, but it is constantly constructed and adapted through experience.

Behavioral and neural correlates of perceived and imagined musical timbre

The generality of findings implicating secondary auditory areas in auditory imagery was tested by using a timbre imagery task with fMRI. Another aim was to test whether activity in supplementary motor area (SMA) seen in prior studies might have been related to subvocalization. Participants with moderate musical background were scanned while making similarity judgments about the timbre of heard or imagined musical instrument sounds. The critical control condition was a visual imagery task. The pattern of judgments in perceived and imagined conditions was similar, suggesting that perception and imagery access similar cognitive representations of timbre. As expected, judgments of heard timbres, relative to the visual imagery control, activated primary and secondary auditory areas with some right-sided asymmetry. Timbre imagery also activated secondary auditory areas relative to the visual imagery control, although less strongly, in accord with previous data. Significant overlap was observed in these regions between perceptual and imagery conditions. Because the visual control task resulted in deactivation of auditory areas relative to a silent baseline, we interpret the timbre imagery effect as a reversal of that deactivation. Despite the lack of an obvious subvocalization component to timbre imagery, some activity in SMA was observed, suggesting that SMA may have a more general role in imagery beyond any motor component.

Brain responses to auditory and visual stimulus offset: Shared representations of temporal edges

Edges are crucial for the formation of coherent objects from sequential sensory inputs within a single modality. Moreover, temporally coincident boundaries of perceptual objects across different sensory modalities facilitate crossmodal integration. Here, we used functional magnetic resonance imaging in order to examine the neural basis of temporal edge detection across modalities. Onsets of sensory inputs are not only related to the detection of an edge but also to the processing of novel sensory inputs. Thus, we used transitions from input to rest (offsets) as convenient stimuli for studying the neural underpinnings of visual and acoustic edge detection per se. We found, besides modality-specific patterns, shared visual and auditory offset-related activity in the superior temporal sulcus and insula of the right hemisphere. Our data suggest that right hemispheric regions known to be involved in multisensory processing are crucial for detection of edges in the temporal domain across both visual and auditory modalities. This operation is likely to facilitate cross-modal object feature binding based on temporal coincidence. Hum Brain Mapp, 2008. (c) 2008 Wiley-Liss, Inc.

Exploring the emotional brain: Neural correlates of homeostatic and sensory-evoked emotions and their interaction in emotional rivalry

Human emotions are essential for survival. They are vital for the satisfaction of basic needs, the regulation of personal life and successful integration into social structures. Depending on which aspect of an emotion is used in its definition, many different theories offer possible answers to the questions of what emotions are and how they can be distinguished. The systematic investigation of emotions in cognitive neuroscience is relatively new, and neuroimaging studies specifically focussing on the neural correlates of different categories of emotions are still lacking. Therefore, the current thesis aimed at investigating the behavioural and neurophysiological correlates of different human emotional levels and their interaction in healthy subjects. We differentiated between emotions according to their cerebral entry site and neural processing pathways: homeostatic emotions, which are elicited by metabolic changes and processed by the interoceptive system (such as thirst, hunger, and need for air), and sensory-evoked emotions, which are evoked by external inputs via the eyes, ears or nose, or their corresponding mental representations and processed in the brain as sensory perception (e.g. fear, disgust, or pride). Using functional magnetic resonance imaging (fMRI) and behavioural parameters, we examined both the specific neural underpinnings of a homeostatic emotion (thirst) and a sensory-evoked emotion (disgust), and their interaction in a situation of emotional rivalry when both emotions were perceived simultaneously. This thesis comprises three research articles reporting the results of this research. The first paper presents disgust-related brain imaging data in a thirsty and a satiated condition. We found that disgust mainly activated the anterior insular cortex. In the thirsty condition, however, we observed an interaction effect between disgust and thirst: when thirsty, the subjects rated the disgusting stimulus as less repulsive. On the neurobiological level, this reduction of subjective disgust was accompanied by significantly reduced neural activity in the insular cortex. These results provide new neurophysiological evidence for a hierarchical organization among homeostatic and sensory-evoked emotions, revealing that in a situation of emotional conflict, homeostatic emotions are prioritized over sensory-evoked emotions. In the second paper, findings on brain perfusion over four different thirst stages are reported, with a special focus on the parametric progression of thirst. Cerebral perfusion differences over all thirst stages were found in the posterior insular cortex. Taking this result together with the findings of the first paper, the insular cortex seems to be a key player in human emotional processing, since it comprises specific representations of homeostatic and sensory-evoked emotions and also represents the site of cortical interaction between the two levels of emotions. Finally, although this thesis focussed on the homeostatic modulation of disgust, we were also interested in whether dehydration modulates taste perception. The results of this behavioural experiment are described in the third paper, where we show that dehydration alters the perception of neutral taste stimuli.

Learning -dependent plasticity of movement representations in the primate primary motor cortex

Primary motor cortex (M1) is involved in the production of voluntary movement and contains a complete functional representation, or map, of the skeletal musculature. This functional map can be altered by pathological experiences, such as peripheral nerve injury or stroke, by pharmacological manipulation, and by behavioral experience. The process by which experience-dependent alterations of cortical function occur is termed plasticity. In this thesis, plasticity of M1 functional organization as a consequence of behavioral experience was examined in adult primates (squirrel monkeys). Maps of movement representations were derived under anesthesia using intracortical microstimulation, whereby a microelectrode was inserted into the cortex to electrically stimulate corticospinal neurons at low current levels and evoke movements of the forelimb, principally of the hand. Movement representations were examined before and at several times after training on behavioral tasks that emphasized use of the fingers. Two behavioral tasks were utilized that dissociated the repetition of motor activity from the acquisition of motor skills. One task was easy to perform, and as such promoted repetitive motor activity without learning. The other task was more difficult, requiring the acquisition of motor skills for successful performance. Kinematic analysis indicated that monkeys used a consistent set of forelimb movements during pellet extractions. Functional mapping revealed that repetitive motor activity during the easier task did not produce plastic changes in movement representations. Instead, map plasticity, in the form of selective expansions of task-related movement representations, was only produced following skill acquisition on the difficult task. Additional studies revealed that, in general, map plasticity persisted without further training for up to three months, in parallel with the retention of task-related motor skills. Also, extensive additional training on the small well task produced further improvements in performance, and further changes in movement maps. In sum, these experiments support the following three conclusions regarding the role of M1 in motor learning. First, behaviorally-driven plasticity is learning-dependent, not activity-dependent. Second, plastic changes in M1 functional representations represent a neural correlate of acquired motor skills. Third, the persistence of map plasticity suggests that M1 is part of the neural substrate for the memory of motor skills. ^