Biology subjects

Nakatani, M.

Publications and source records attributed to Nakatani, M..

3 recordsLinked to original sources

bioRxiv2020

Carbamazepine and GABA have distinct effects on seizure onset dynamics in mouse brain slices

Optimizing antiepileptic drug therapy is very challenging due to the absence of a reliable method to assess how brain activity changes between seizures. This work uses the Taxonomy of Seizure Dynamics (Saggio et al., 2020) to investigate how anticonvulsants influence seizure onset dynamotypes. The no Mg2+ /high K+ mouse brain-slice seizure model (N = 92) was used to generate consistent epileptiform onsets. We compared the onset bifurcations of controls with slices treated with either GABA or carbamazepine. Each anticonvulsant uniquely changed the types of bifurcations in the slices. This experiment provides proof-of-concept evidence that brain states exist on a "map" of seizure dynamics, and that antiepileptic drugs with different mechanisms can change the positioning of the brain states on the map. Impact statementAntiepileptic drugs modify underlying brain states and influence the pathway into seizure onset in brain slices.

bioinformatics↗

bioRxiv2020

Epidynamics characterize and navigate the map of seizure dynamics

Seizures are a disruption of normal brain activity present across a vast range of species, diseases, and conditions. Here we introduce an organizing principle that leads to the first objective Taxonomy of Seizure Dynamics (TSD) based on bifurcation theory, and applied it to the analysis of EEG data. The "dynamotype" of a seizure is the part of its dynamic composition that defines its observable characteristics, including how it starts, evolves and terminates. Analyzing over 2000 focal-onset seizures recorded from 7 epilepsy centers on five continents, we find evidence of all 16 dynamotypes predicted in TSD. We demonstrate that patients dynamotypes evolve during their lifetime and display complex but systematic variations including hierarchy (certain dynamotypes are more common), non-bijectivity (a patient may display multiple dynamotypes) and pairing preference (multiple dynamotypes may occur during one seizure). TSD not only provides a way to stratify patients in complement to present practical classifications but also guides biophysically based mechanistic approaches and provides a language to describe the most critical features of seizure dynamics. Impact statementTaxonomy of Seizure Dynamics (TSD) provides a rigorous method for classifying and quantifying seizures and a principled framework for understanding seizure initiation and propagation.

bioinformatics↗

bioRxiv2019

Deep, soft, and dark sounds induce autonomous sensory meridian response

There has been a growing interest in the autonomous sensory meridian response (ASMR). The ASMR is characterized by a tingling sensation around the scalp and neck and often induces a feeling of relaxation and a reduction of a negative mood. However, it is still unknown what factors affect the ASMR. The present study focused on stimulus characteristics and individuals mood states and personality traits. Participants filled out self-reported questionnaires (the Profile of Mood States, Beck Depression Inventory, and Big Five Inventory) and reported ASMR estimates throughout a 17-min experiment while listening to binaural tapping and brushing sounds. Cross-correlation results showed that the ASMR estimates were strongly associated with the acoustic features of auditory stimuli, such as their amplitude, spectral centroid, and spectral bandwidth. This indicates that low-pitched sounds with dark timbre trigger the ASMR. The maximum ASMR was observed around 2 s after the acoustic features changed, suggesting that the sluggishness of multisensory integration may lead to the ASMR experience. In addition, individual differences in the ASMR experience were closely linked to participants mood states, such as anxiety, but not to their personality traits. Our results provide important clues to understand the mechanisms of auditory-somatosensory interactions. Significant StatementsThe autonomous sensory meridian response (ASMR) is characterized by a tingling, electrostatic-like sensation across the scalp and back of the neck. This phenomenon can be triggered by a variety of audiovisual stimuli, and many people seek out the ASMR via the internet to receive a feeling of relaxation and reduce a negative mood. We show that the ASMR is induced about 2 s after acoustic features, such as the amplitude, spectral centroid, and spectral bandwidth are changed. This suggests that low-pitched sounds with dark timbre lead to the ASMR experience. The stimulus-driven ASMR effect is found regardless of the personality traits or mood states of participants. Our findings provide a critical clue to understand the mechanisms of auditory-somatosensory interactions.

neuroscience↗