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  • 1.
    Cartling, Bo
    KTH, School of Engineering Sciences (SCI), Physics.
    Beating frequency and amplitude modulation of the piano tone due to coupling of tones2005In: Journal of the Acoustical Society of America, ISSN 0001-4966, E-ISSN 1520-8524, Vol. 117, no 4, p. 2259-2267Article in journal (Refereed)
    Abstract [en]

    The influence on a piano tone from weak coexcitation of damped adjacent tones due to coupling via the bridge is studied. The frequency and amplitude modulation of the sound resulting from coexcitation of one strong and one or two weak tones is analyzed. One weak tone causes frequency and amplitude modulation of the sound, and two weak tones produce beating frequency and amplitude modulation, where the beatings of the two modulations are of opposite phase. By digital recording of the sound of piano tones, the appearance of these phenomena is verified. The audibility of the observed frequency and amplitude modulation is discussed in terms of previously determined detection thresholds. The beating character of both frequency and amplitude modulations, however, distinguishes the phenomena from those previously studied and prompts further psychoacoustic investigations. It is shown that detuning of unison strings may significantly increase the frequency deviation of the frequency modulation in conjunction with affected amplitude modulation. The modulatory effects of coupling to adjacent tones therefore may possibly be utilized in the tuning process. A coupling of tones analogous to the situation in a piano may arise in other stringed musical instruments transferring string vibrations to a soundboard via a bridge.

  • 2.
    Cartling, Bo
    KTH, Superseded Departments, Physics.
    Control of neural information transmission by synaptic dynamics2002In: Journal of Theoretical Biology, ISSN 0022-5193, E-ISSN 1095-8541, Vol. 214, no 2, p. 275-292Article in journal (Refereed)
    Abstract [en]

    The computational processing of a neural system is strongly influenced by the dynamical characteristics of the information transmission between neurons. In this work, the control of neural information transmission by synaptic dynamics is investigated by means of a master-equation-based stochastic model of pre-synaptic release of neurotransmitter-containing vesicles. The model incorporates facilitation of vesicle fusion with the pre-synaptic membrane due to intracellular calcium ions and depletion of readily releasable vesicles. The message to be transmitted is coded by the pre-synaptic firing sequence, and the received signal corresponds to the post-synaptic membrane potential response. At the sending end, the stochastic character of the vesicle release contributes to the entropy of the probability distribution of the number of vesicles released and represents noise with respect to information transmission. At the receiving end, the generation of post-synaptic membrane potentials is influenced by the temporal behaviour of ionic currents and membrane charging and is determined by means of a low-dimensional model. The rate and temporal types of neural coding are compatible with limiting cases of the synaptic information transmission as a function of initial vesicle release probability and pre-synaptic firing rate. The effects of the nonlinear dependencies of the vesicle release probability on intracellular calcium concentration and number of available vesicles are analysed. The model is compared with phenomenological and reduced models, a principal advantage being the capability of also determining fluctuations of dynamic variables.

  • 3.
    Cartling, Bo
    KTH, School of Engineering Sciences (SCI), Physics.
    Neuromodulatory control of interacting medial temporal lobe and neocortex in memory consolidation and working memory2001In: Behavioural Brain Research, ISSN 0166-4328, E-ISSN 1872-7549, Vol. 126, p. 65-80Article in journal (Refereed)
  • 4.
    Cartling, Bo
    KTH, Superseded Departments, Physics.
    Neuromodulatory control of neocortical microcircuits with activity-dependent short-term synaptic depression2004In: Journal of biological physics (Print), ISSN 0092-0606, E-ISSN 1573-0689, Vol. 30, no 3, p. 261-284Article in journal (Refereed)
    Abstract [en]

    A biophysical model of a neocortical microcircuit system is formulated and employed in studies of neuromodulatory control of dynamics and function. The model is based on recent observations of reciprocal connections between pyramidal cells and inhibitory interneurons and incorporates a new type of activity-dependent short-term depression of synaptic couplings recently observed. The model neurons are of a low-dimensional type also accounting for neuronal adaptation, i.e. the coupling between neuronal activity and excitability, which can be regulated by various neuromodulators in the brain. The results obtained demonstrate a capacity for neuromodulatory control of dynamical mode linked to functional mode. The functional aspects considered refer to the observed resolution of multiple objects in working memory as well as the binding of different features for the perception of an object. The effects of neuromodulators displayed by the model are in accordance with many observations on neuromodulatory influence on cognitive functions and brain disorders.

  • 5.
    Cartling, Bo
    KTH, School of Engineering Sciences (SCI), Theoretical Physics, Statistical Physics.
    On the implicit acquisition of a context-free grammar by a simple recurrent neural network2008In: Neurocomputing, ISSN 0925-2312, E-ISSN 1872-8286, Vol. 71, no 7-9, p. 1527-1537Article in journal (Refereed)
    Abstract [en]

    The performance of a simple recurrent neural network on the implicit acquisition of a context-free grammar is re-examined and found to be significantly higher than previously reported by Elman. This result is obtained although the previous work employed it multilayer extension of the basic form of simple recurrent network and restricted the complexity of training and test corpora. The high performance is traced to a well-organized internal representation of the grammatical elements, as probed by a principal-component analysis of the hidden-layer activities. From the next-symbol-prediction performance on sentences not present in the training corpus, it capacity of generalization is demonstrated.

  • 6.
    Cartling, Bo
    KTH, Superseded Departments, Physics.
    Stochastic and reduced biophysical models of synaptic transmission2000In: Journal of biological physics (Print), ISSN 0092-0606, E-ISSN 1573-0689, Vol. 26, no 2, p. 113-131Article in journal (Refereed)
    Abstract [en]

    Stochastic and reduced biophysical models of synaptic transmission are formulated and evaluated. The synaptic transmission involves presynaptic facilitation of neurotransmitter release, depletion and recovery of the presynaptic pool of readily releasable vesicles containing neurotransmitter molecules and saturation of postsynaptic receptors of both fast non-NMDA and slow NMDA types. The models are shown to display the principal dynamical characteristics experimentally observed of synaptic transmission. The two main types of neural coding, i.e. rate and temporal coding, can be distinguished by means of different dynamical properties of synaptic transmission determined by initial neurotransmitter release probability and presynaptic firing rate. From the temporal evolution of the postsynaptic membrane potential response to a train of presynaptic action potentials at a sustained firing rate, in particular the steady-state amplitude and steady-state average level of postsynaptic membrane potentials are determined as functions of both initial release probability and presynaptic firing rate. The models are applicable to studies of the primary stages of learning processes and can be extended to incorporate short-term and long-term potentiation in memory consolidation processes.

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