The multidimensional nature of the frontal lobes serves to organize and coordinate brain functioning, playing a central and pervasive role in human cognition. The organizational and strategic nature of frontal lobe functioning affects memory processes by enhancing the organization of to-be-remembered information. Among the specific memory systems presumed to be based on anterior cerebral structures is the temporal organization of memory. An essential component of memory that involves temporal organization is sequential ordering. The acquisition of abilities thought to be mediated by the frontal lobes, including sequential memory, unfolds throughout childhood, serving to condition patterns of behavior for the rest of the brain. Development of the frontal regions of the brain is known to continue through late adolescence and into early adulthood, in contrast to the earlier maturation of other cortical regions. The purpose of the present study was to evaluate the development of sequential memory and to compare such findings to what currently is known regarding the development of frontal lobe functioning. Through an analysis of the previously collected standardization data of the Test of Memory and Learning (TOMAL; Reynolds & Bigler, 1994), a developmental function depicting the maturational process of sequential memory was derived. This model was then compared to an overall representative model of frontal lobe functioning. Results indicated a staging of development that begins in early childhood with the maturation of sequential memory continuing, although at a decreased rate, into early adolescence. The greatest period of development in sequential memory was evident between 5 and 8 years of age. The rate of development then decreased, and a continued deceleration of maturation continued throughout the age span examined. Gender was not found to be a significant predictor of developmental performance on sequential memory tasks. The results of the present study are consistent with previous findings that have suggested that the development of frontal functions occurs in a step-wise fashion with greatest period of development in frontal lobe functioning occurring at the 6- and 8-year old levels, with more moderate effects between the ages of 9 and 12 and performance approximating adult levels during adolescence.

Sequential structure imposed by the forward linear progression of time is omnipresent in all cognitive behaviors. This thesis proposes a novel model to store sequences of any length, scalar or vectorial, in binary neural networks. Particularly, the model that we introduce allows resolving some well known problems in sequential learning, such as error intolerance, catastrophic forgetting and the interference issue while storing complex sequences, etc. The quantity of the total sequential information that the network is able to store grows quadratically with the number of nodes. And the efficiency - the ratio between the capacity and the total amount of information consumed by the storage device - can reach around 30%. This work could be considered as an extension of the non oriented clique-based neural networks previously proposed and studied within our team. Those networks composed of binary neurons and binary connections utilize the concept of graph redundancy and sparsity in order to acquire a quadratic learning diversity. To obtain the ability to store sequences, connections are provided with orientation to form a tournament-based neural network. This is more natural biologically speak- ing, since communication between neurons is unidirectional, from axons to synapses. Any component of the network, a cluster or a node, can be revisited several times within a sequence or by multiple sequences. This allows the network to store se- quences of any length, independent of the number of clusters and only limited by the total available resource of the network. Moreover, in order to allow error correction and provide robustness to the net- work, both spatial assembly redundancy and sequential redundancy, with or without anticipation, may be combined to offer a large amount of redundancy in the activation of a node. Subsequently, a double layered structure is introduced with the purpose of accurate retrieval. The lower layer of tournament-based hetero-associative network stores sequential oriented associations between patterns. An upper auto-associative layer of mirror nodes is superposed to emphasize the co-occurrence of the elements belonging to the same pattern, in the form of a clique. This model is then extended to a hierarchical structure, which helps resolve the interference issue while storing complex sequences. This thesis also contributes in proposing and assessing new decoding rules with respect to sparse messages in order to fully benefit from the theoretical quadratic law of the learning diversity. Besides the performance aspect, the biological plausibility is also a constant concern during this thesis work.