Current hypotheses suggest that speech segmentation-the initial division and grouping of the speech stream into candidate phrases, syllables, and phonemes for further linguistic processing-is executed by a hierarchy of oscillators in auditory cortex. Theta (∼3-12 Hz) rhythms play a key role by phase-locking to recurring acoustic features marking syllable boundaries. Reliable synchronization to quasi-rhythmic inputs, whose variable frequency can dip below cortical theta frequencies (down to ∼1 Hz), requires "flexible" theta oscillators whose underlying neuronal mechanisms remain unknown. Using biophysical computational models, we found that the flexibility of phase-locking in neural oscillators depended on the types of hyperpolarizing currents that paced them. Simulated cortical theta oscillators flexibly phase-locked to slow inputs when these inputs caused both (i) spiking and (ii) the subsequent buildup of outward current sufficient to delay further spiking until the next input. The greatest flexibility in phase-locking arose from a synergistic interaction between intrinsic currents that was not replicated by synaptic currents at similar timescales. Flexibility in phase-locking enabled improved entrainment to speech input, optimal at mid-vocalic channels, which in turn supported syllabic-timescale segmentation through identification of vocalic nuclei. Our results suggest that synaptic and intrinsic inhibition contribute to frequency-restricted and -flexible phase-locking in neural oscillators, respectively. Their differential deployment may enable neural oscillators to play diverse roles, from reliable internal clocking to adaptive segmentation of quasi-regular sensory inputs like speech.
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http://dx.doi.org/10.1371/journal.pcbi.1008783 | DOI Listing |
Prog Neurobiol
January 2025
Department of Biomedicine, University of Basel, Klingelbergstrasse 50, 4056 Basel, Switzerland. Electronic address:
The brain faces the challenging task of preserving a consistent portrayal of the external world in the face of disruptive sensory inputs. What alterations occur in sensory representation amidst noise, and how does brain activity adapt to it? Although it has previously been shown that background white noise (WN) decreases responses to salient sounds, a mechanistic understanding of the brain processes responsible for such changes is lacking. We investigated the effect of background WN on neuronal spiking activity, membrane potential, and network oscillations in the mouse central auditory system.
View Article and Find Full Text PDFJ Clin Med
January 2025
Faculty of Physical Culture and Health, Institute of Physical Culture Sciences, University of Szczecin, Al. Piastów 40B blok 6, 71-065 Szczecin, Poland.
Amyotrophic lateral sclerosis (ALS) is a complex, progressive neurodegenerative disorder characterized by the degeneration of motor neurons in the brain, brainstem, and spinal cord. Several neuroimaging techniques can help reveal the pathophysiology of ALS. One of these is the electroencephalogram (EEG), a noninvasive and relatively inexpensive tool for examining electrical activity of the brain with excellent temporal precision.
View Article and Find Full Text PDFBiology (Basel)
January 2025
School of Instrumentation Science and Optoelectronic Engineering, Beihang University, Beijing 100191, China.
Neural oscillations observed during semantic processing embody the function of brain language processing. Precise parameterization of the differences in these oscillations across various semantics from a time-frequency perspective is pivotal for elucidating the mechanisms of brain language processing. The superlet transform and cluster depth test were used to compute the time-frequency representation of oscillatory difference (ODTFR) between neural activities recorded by optically pumped magnetometer-based magnetoencephalography (OPM-MEG) during processing congruent and incongruent Chinese semantics.
View Article and Find Full Text PDFNeural Netw
January 2025
Department of Mathematical Sciences, Rajiv Gandhi Institute of Petroleum Technology, Jais, Amethi, Uttar Pradesh, 229304, India. Electronic address:
In this paper, we introduce the concept of (ω,c)-asymptotic periodicity within the context of translation-invariant time scales. This concept generalizes various types of function, including asymptotically periodic, asymptotically antiperiodic, asymptotically Bloch periodic, and certain unbounded functions on time scales. We investigate some fundamental properties of this class of functions and apply our findings to cellular neural network (CNN) dynamic equations with leakage and mixed time-varying delays.
View Article and Find Full Text PDFEur J Neurosci
January 2025
Department of Psychology, University of Lübeck, Lübeck, Germany.
Distraction is ubiquitous in human environments. Distracting input is often predictable, but we do not understand when or how humans can exploit this predictability. Here, we ask whether predictable distractors are able to reduce uncertainty in updating the internal predictive model.
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