Controllo dell'atto di prensione: coinvolgimento dell'area V6A nell'orientamento del polso

Prehension in an act of coordinated reaching and grasping. The reaching component is concerned with bringing the hand to object to be grasped (transport phase); the grasping component refers to the shaping of the hand according to the object features (grasping phase) (Jeannerod, 1981). Reaching and grasping involve different muscles, proximal and distal muscles respectively, and are controlled by different parietofrontal circuit (Jeannerod et al., 1995): a medial circuit, involving area of superior parietal lobule and dorsal premotor area 6 (PMd) (dorsomedial visual stream), is mainly concerned with reaching; a lateral circuit, involving the inferior parietal lobule and ventral premotor area 6 (PMv) (dorsolateral visual stream), with grasping. Area V6A is located in the caudalmost part of the superior parietal lobule, so it belongs to the dorsomedial visual stream; it contains neurons sensitive to visual stimuli (Galletti et al. 1993, 1996, 1999) as well as cells sensitive to the direction of gaze (Galletti et al. 1995) and cells showing saccade-related activity (Nakamura et al. 1999; Kutz et al. 2003). Area V6A contains also arm-reaching neurons likely involved in the control of the direction of the arm during movements towards objects in the peripersonal space (Galletti et al. 1997; Fattori et al. 2001). The present results confirm this finding and demonstrate that during the reach-to-grasp the V6A neurons are also modulated by the orientation of the wrist. Experiments were approved by the Bioethical Committee of the University of Bologna and were performed in accordance with National laws on care and use of laboratory animals and with the European Communities Council Directive of 24th November 1986 (86/609/EEC), recently revised by the Council of Europe guidelines (Appendix A of Convention ETS 123). Experiments were performed in two awake Macaca fascicularis. Each monkey was trained to sit in a primate chair with the head restrained to perform reaching and grasping arm movements in complete darkness while gazing a small fixation point. The object to be grasped was a handle that could have different orientation. We recorded neural activity from 163 neurons of the anterior parietal sulcus; 116/163 (71%) neurons were modulated by the reach-to-grasp task during the execution of the forward movements toward the target (epoch MOV), 111/163 (68%) during the pulling of the handle (epoch HOLD) and 102/163 during the execution of backward movements (epoch M2) (t_test, p ≤ 0.05). About the 45% of the tested cells turned out to be sensitive to the orientation of the handle (one way ANOVA, p ≤ 0.05). To study how the distal components of the movement, such as the hand preshaping during the reaching of the handle, could influence the neuronal discharge, we compared the neuronal activity during the reaching movements towards the same spatial location in reach-to-point and reach-to-grasp tasks. Both tasks required proximal arm movements; only the reach-to-grasp task required distal movements to orient the wrist and to shape the hand to grasp the handle. The 56% of V6A cells showed significant differences in the neural discharge (one way ANOVA, p ≤ 0.05) between the reach-to-point and the reach-to-grasp tasks during MOV, 54% during HOLD and 52% during M2. These data show that reaching and grasping are processed by the same population of neurons, providing evidence that the coordination of reaching and grasping takes place much earlier than previously thought, i.e., in the parieto-occipital cortex. The data here reported are in agreement with results of lesions to the medial posterior parietal cortex in both monkeys and humans, and with recent imaging data in humans, all of them indicating a functional coupling in the control of reaching and grasping by the medial parietofrontal circuit.

Mathematical models of cognitive processes

The research activity carried out during the PhD course was focused on the development of mathematical models of some cognitive processes and their validation by means of data present in literature, with a double aim: i) to achieve a better interpretation and explanation of the great amount of data obtained on these processes from different methodologies (electrophysiological recordings on animals, neuropsychological, psychophysical and neuroimaging studies in humans), ii) to exploit model predictions and results to guide future research and experiments. In particular, the research activity has been focused on two different projects: 1) the first one concerns the development of neural oscillators networks, in order to investigate the mechanisms of synchronization of the neural oscillatory activity during cognitive processes, such as object recognition, memory, language, attention; 2) the second one concerns the mathematical modelling of multisensory integration processes (e.g. visual-acoustic), which occur in several cortical and subcortical regions (in particular in a subcortical structure named Superior Colliculus (SC)), and which are fundamental for orienting motor and attentive responses to external world stimuli. This activity has been realized in collaboration with the Center for Studies and Researches in Cognitive Neuroscience of the University of Bologna (in Cesena) and the Department of Neurobiology and Anatomy of the Wake Forest University School of Medicine (NC, USA). PART 1. Objects representation in a number of cognitive functions, like perception and recognition, foresees distribute processes in different cortical areas. One of the main neurophysiological question concerns how the correlation between these disparate areas is realized, in order to succeed in grouping together the characteristics of the same object (binding problem) and in maintaining segregated the properties belonging to different objects simultaneously present (segmentation problem). Different theories have been proposed to address these questions (Barlow, 1972). One of the most influential theory is the so called “assembly coding”, postulated by Singer (2003), according to which 1) an object is well described by a few fundamental properties, processing in different and distributed cortical areas; 2) the recognition of the object would be realized by means of the simultaneously activation of the cortical areas representing its different features; 3) groups of properties belonging to different objects would be kept separated in the time domain. In Chapter 1.1 and in Chapter 1.2 we present two neural network models for object recognition, based on the “assembly coding” hypothesis. These models are networks of Wilson-Cowan oscillators which exploit: i) two high-level “Gestalt Rules” (the similarity and previous knowledge rules), to realize the functional link between elements of different cortical areas representing properties of the same object (binding problem); 2) the synchronization of the neural oscillatory activity in the γ-band (30-100Hz), to segregate in time the representations of different objects simultaneously present (segmentation problem). These models are able to recognize and reconstruct multiple simultaneous external objects, even in difficult case (some wrong or lacking features, shared features, superimposed noise). In Chapter 1.3 the previous models are extended to realize a semantic memory, in which sensory-motor representations of objects are linked with words. To this aim, the network, previously developed, devoted to the representation of objects as a collection of sensory-motor features, is reciprocally linked with a second network devoted to the representation of words (lexical network) Synapses linking the two networks are trained via a time-dependent Hebbian rule, during a training period in which individual objects are presented together with the corresponding words. Simulation results demonstrate that, during the retrieval phase, the network can deal with the simultaneous presence of objects (from sensory-motor inputs) and words (from linguistic inputs), can correctly associate objects with words and segment objects even in the presence of incomplete information. Moreover, the network can realize some semantic links among words representing objects with some shared features. These results support the idea that semantic memory can be described as an integrated process, whose content is retrieved by the co-activation of different multimodal regions. In perspective, extended versions of this model may be used to test conceptual theories, and to provide a quantitative assessment of existing data (for instance concerning patients with neural deficits). PART 2. The ability of the brain to integrate information from different sensory channels is fundamental to perception of the external world (Stein et al, 1993). It is well documented that a number of extraprimary areas have neurons capable of such a task; one of the best known of these is the superior colliculus (SC). This midbrain structure receives auditory, visual and somatosensory inputs from different subcortical and cortical areas, and is involved in the control of orientation to external events (Wallace et al, 1993). SC neurons respond to each of these sensory inputs separately, but is also capable of integrating them (Stein et al, 1993) so that the response to the combined multisensory stimuli is greater than that to the individual component stimuli (enhancement). This enhancement is proportionately greater if the modality-specific paired stimuli are weaker (the principle of inverse effectiveness). Several studies have shown that the capability of SC neurons to engage in multisensory integration requires inputs from cortex; primarily the anterior ectosylvian sulcus (AES), but also the rostral lateral suprasylvian sulcus (rLS). If these cortical inputs are deactivated the response of SC neurons to cross-modal stimulation is no different from that evoked by the most effective of its individual component stimuli (Jiang et al 2001). This phenomenon can be better understood through mathematical models. The use of mathematical models and neural networks can place the mass of data that has been accumulated about this phenomenon and its underlying circuitry into a coherent theoretical structure. In Chapter 2.1 a simple neural network model of this structure is presented; this model is able to reproduce a large number of SC behaviours like multisensory enhancement, multisensory and unisensory depression, inverse effectiveness. In Chapter 2.2 this model was improved by incorporating more neurophysiological knowledge about the neural circuitry underlying SC multisensory integration, in order to suggest possible physiological mechanisms through which it is effected. This endeavour was realized in collaboration with Professor B.E. Stein and Doctor B. Rowland during the 6 months-period spent at the Department of Neurobiology and Anatomy of the Wake Forest University School of Medicine (NC, USA), within the Marco Polo Project. The model includes four distinct unisensory areas that are devoted to a topological representation of external stimuli. Two of them represent subregions of the AES (i.e., FAES, an auditory area, and AEV, a visual area) and send descending inputs to the ipsilateral SC; the other two represent subcortical areas (one auditory and one visual) projecting ascending inputs to the same SC. Different competitive mechanisms, realized by means of population of interneurons, are used in the model to reproduce the different behaviour of SC neurons in conditions of cortical activation and deactivation. The model, with a single set of parameters, is able to mimic the behaviour of SC multisensory neurons in response to very different stimulus conditions (multisensory enhancement, inverse effectiveness, within- and cross-modal suppression of spatially disparate stimuli), with cortex functional and cortex deactivated, and with a particular type of membrane receptors (NMDA receptors) active or inhibited. All these results agree with the data reported in Jiang et al. (2001) and in Binns and Salt (1996). The model suggests that non-linearities in neural responses and synaptic (excitatory and inhibitory) connections can explain the fundamental aspects of multisensory integration, and provides a biologically plausible hypothesis about the underlying circuitry.

Demersal communities in the Mediterranean Sea: a case study of Triglidae (Osteichthyes, Scorpaeniformes) on the conservation and sustainable use of marine resources

An appropriate management of fisheries resources can only be achieved with the continuous supply of information on the structure and biology of populations, in order to predict the temporal fluctuations. This study supports the importance of investigating the bio-ecology of increasingly exploited and poorly known species, such as gurnards (Osteichthyes, Triglidae) from Adriatic Sea (Mediterranean), to quantify their ecological role into marine community. It also focuses on investigate inter and intra-specific structuring factor of Adriatic population. These objectives were achieved by: 1) investigating aspects of the population dynamics; 2) studying the feeding biology through the examination of stomach contents; 3) using sagittal otoliths as potential marker of species life cycle; 4) getting preliminary data on mDNA phylogeny. Gurnards showed a specie-specific “critical size” coinciding with the start of sexual maturity, the tendency to migrate to greater depths, a change of diet from crustaceans to fish and an increase of variety of food items eaten. Distribution of prey items, predator size range and depth distribution were the main dimensions that influence the breadth of trophic niche and the relative difference amongst Adriatic gurnards. Several feeding preferences were individuated and a possible impact among bigger-size gurnards and other commercial fishes (anchovy, gadoids) and Crustacea (such as mantis prawn and shrimps) were to be necessary considered. Otolith studies showed that gurnard species have a very fast growth despite other results in other areas; intra-specific differences and the increase in the variability of otolith shape, sulcus acusticus shape, S:O ratios, sulcus acusticus external crystals arrangement were shown between juveniles and adults and were linked to growth (individual genetic factors) and to environmental conditions (e.g. depth and trophic niche distribution). In order to facilitate correct biological interpretation of data, molecular data were obtained for comparing morphological distance to genetic ones.