3,252 research outputs found
Sequence learning recodes cortical representations instead of strengthening initial ones.
We contrast two computational models of sequence learning. The associative learner posits that learning proceeds by strengthening existing association weights. Alternatively, recoding posits that learning creates new and more efficient representations of the learned sequences. Importantly, both models propose that humans act as optimal learners but capture different statistics of the stimuli in their internal model. Furthermore, these models make dissociable predictions as to how learning changes the neural representation of sequences. We tested these predictions by using fMRI to extract neural activity patterns from the dorsal visual processing stream during a sequence recall task. We observed that only the recoding account can explain the similarity of neural activity patterns, suggesting that participants recode the learned sequences using chunks. We show that associative learning can theoretically store only very limited number of overlapping sequences, such as common in ecological working memory tasks, and hence an efficient learner should recode initial sequence representations
Making tools and making sense: complex, intentional behaviour in human evolution
Stone tool-making is an ancient and prototypically human skill characterized by multiple levels of intentional organization. In a formal sense, it displays surprising similarities to the multi-level organization of human language. Recent functional brain imaging studies of stone tool-making similarly demonstrate overlap with neural circuits involved in language processing. These observations consistent with the hypothesis that language and tool-making share key requirements for the construction of hierarchically structured action sequences and evolved together in a mutually reinforcing way
Music adapting to the brain: From diffusion chains to neurophysiology
During the last decade, the use of experimental approaches on cultural evolution
research has provided novel insights, and supported theoretical predictions, on the
principles driving the evolution of human cultural systems. Laboratory simulations of
language evolution showed how general-domain constraints on learning, in addition to
pressures for language to be expressive, may be responsible for the emergence of
linguistic structure. Languages change when culturally transmitted, adapting to fit,
among all, the cognitive abilities of their users. As a result, they become regular and
compressed, easier to acquire and reproduce. Although a similar theory has been
recently extended to the musical domain, the empirical investigation in this field is still
scarce. In addition, no study to our knowledge directly addressed the role of cognitive
constraints in cultural transmission with neurophysiological investigation.
In my thesis I addressed both these issues with a combination of behavioral and
neurophysiological methods, in three experimental studies. In study 1 (Chapter 2), I
examined the evolution of structural regularities in artificial melodic systems while they
were being transmitted across individuals via coordination and alignment. To this
purpose I used a new laboratory model of music transmission: the multi-generational
signaling games (MGSGs), a variant of the signaling games. This model combines
classical aspects of lab-based semiotic models of communication, coordination and
interaction (horizontal transmission), with the vertical transmission across generations
of the iterated learning model (vertical transmission). Here, two-person signaling games
are organized in diffusion chains of several individuals (generations). In each game, the
two players (a sender and a receiver) must agree on a common code - here a miniature
system where melodic riffs refer to emotions. The receiver in one game becomes the
sender in the next game, possibly retransmitting the code previously learned to another
generation of participants, and so on to complete the diffusion chain. I observed the
gradual evolution of several structures features of musical phrases over generations:
proximity, continuity, symmetry, and melodic compression. Crucially, these features
are found in most of musical cultures of the world. I argue that we tapped into universal
processing mechanisms of structured sequence processing, possibly at work in the
evolution of real music. In study 2 (Chapter 3), I explored the link between cultural
adaptation and neural information processing. To this purpose, I combined behavioral
and EEG study on 2 successive days. I show that the latency of the mismatch negativity (MMN) recorded in a pre-attentive auditory sequence processing task on day 1, predicts
how well participants learn and transmit an artificial tone system with affective
semantics in two signaling games on day 2. Notably, MMN latencies also predict which
structural changes are introduced by participants into the artificial tone system. In study
3 (Chapter 4), I replicated and extended behavioral and neurophysiological findings on
the temporal domain of music, with two independent experiments. In the first
experiment, I used MGSGs as a laboratory model of cultural evolution of rhythmic
equitone patterns referring to distinct emotions. As a result of transmission, rhythms
developed a universal property of music structure, namely temporal regularity (or
isochronicity). In the second experiment, I anchored this result with neural predictors. I
showed that neural information processing capabilities of individuals, as measured with
the MMN on day 1, can predict learning, transmission, and regularization of rhythmic
patterns in signaling games on day 2. In agreement with study 2, I observe that MMN
brain timing may reflect the efficiency of sensory systems to process auditory patterns.
Functional differences in those systems, across individuals, may produce a different
sensitivity to pressures for regularities in the cultural system. Finally, I argue that neural
variability can be an important source of variability of cultural traits in a population.
My work is the first to systematically describe the emergence of structural properties of
melodic and rhythmic systems in the laboratory, using an explicit game-theoretic model
of cultural transmission in which agents freely interact and exchange information.
Critically, it provides the first demonstration that social learning, transmission, and
cultural adaptation are constrained and driven by individual differences in the functional
organization of sensory systems
Language learning in aphasia: A narrative review and critical analysis of the literature with implications for language therapy
People with aphasia (PWA) present with language deficits including word retrieval difficulties after brain damage. Language learning is an essential life-long human capacity that may support treatment-induced lan-guage recovery after brain insult. This prospect has motivated a growing interest in the study of language learning in PWA during the last few decades. Here, we critically review the current literature on language learning ability in aphasia. The existing studies in this area indicate that (i) language learning can remain functional in some PWA, (ii) inter-individual variability in learning performance is large in PWA, (iii) language processing, short-term memory and lesion site are associated with learning ability, (iv) preliminary evidence suggests a relationship between learning ability and treatment outcomes in this population. Based on the reviewed evidence, we propose a potential account for the interplay between language and memory/learning systems to explain spared/impaired language learning and its relationship to language therapy in PWA. Finally, we indicate potential avenues for future research that may promote more cross-talk between cognitive neuro-science and aphasia rehabilitation
Self-Supervised Vision-Based Detection of the Active Speaker as Support for Socially-Aware Language Acquisition
This paper presents a self-supervised method for visual detection of the
active speaker in a multi-person spoken interaction scenario. Active speaker
detection is a fundamental prerequisite for any artificial cognitive system
attempting to acquire language in social settings. The proposed method is
intended to complement the acoustic detection of the active speaker, thus
improving the system robustness in noisy conditions. The method can detect an
arbitrary number of possibly overlapping active speakers based exclusively on
visual information about their face. Furthermore, the method does not rely on
external annotations, thus complying with cognitive development. Instead, the
method uses information from the auditory modality to support learning in the
visual domain. This paper reports an extensive evaluation of the proposed
method using a large multi-person face-to-face interaction dataset. The results
show good performance in a speaker dependent setting. However, in a speaker
independent setting the proposed method yields a significantly lower
performance. We believe that the proposed method represents an essential
component of any artificial cognitive system or robotic platform engaging in
social interactions.Comment: 10 pages, IEEE Transactions on Cognitive and Developmental System
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