Gamma oscillations are physiological phenomena that reflect perception and cognition, and involve parvalbumin-positive γ-aminobutyric acid-ergic interneuron function. The auditory steady-state response (ASSR) is the most robust index for gamma oscillations, and it is impaired in patients with neuropsychiatric disorders such as schizophrenia and autism. Although ASSR reduction is known to vary in terms of frequency and time, the neural mechanisms are poorly understood. We obtained high-density electrocorticography recordings from a wide area of the cortex in 8 patients with refractory epilepsy. In an ASSR paradigm, click sounds were presented at frequencies of 20, 30, 40, 60, 80, 120, and 160 Hz. We performed time-frequency analyses and analyzed intertrial coherence, event-related spectral perturbation, and high-gamma oscillations. We demonstrate that the ASSR is globally distributed among the temporal, parietal, and frontal cortices. The ASSR was composed of time-dependent neural subcircuits differing in frequency tuning. Importantly, the frequency tuning characteristics of the late-latency ASSR varied between the temporal/frontal and parietal cortex, suggestive of differentiation along parallel auditory pathways. This large-scale survey of the cortical ASSR could serve as a foundation for future studies of the ASSR in patients with neuropsychiatric disorders.
Auditory contextual processing has been assumed to be based on a hierarchical structure consisting of the primary auditory cortex, superior temporal gyrus (STG), and frontal lobe. Recent invasive studies on mismatch negativity (MMN) have revealed functional segregation for auditory contextual processing such as neural adaptation in the primary auditory cortex and prediction in the frontal lobe. However, the role of the STG remains unclear. We obtained induced activity in the high gamma band as mismatch response (MMR), an electrocorticographic (ECoG) counterpart to scalp MMN, and the components of MMR by analyzing ECoG data from patients with refractory epilepsy in an auditory oddball task paradigm. We found that MMR localized mainly in the bilateral posterior STGs, and that deviance detection largely accounted for MMR. Furthermore, adaptation was identified in a limited number of electrodes on the superior temporal plane. Our findings reveal a mixed contribution of deviance detection and adaptation depending on location in the STG. Such spatial considerations could lead to further understanding of the pathophysiology of relevant psychiatric disorders.
Restoration of speech communication for locked-in patients by means of brain computer interfaces (BCIs) is currently an important area of active research. Among the neural signals obtained from intracranial recordings, single/multi-unit activity (SUA/MUA), local field potential (LFP), and electrocorticography (ECoG) are good candidates for an input signal for BCIs. However, the question of which signal or which combination of the three signal modalities is best suited for decoding speech production remains unverified. In order to record SUA, LFP, and ECoG simultaneously from a highly localized area of human ventral sensorimotor cortex (vSMC), we fabricated an electrode the size of which was 7 by 13 mm containing sparsely arranged microneedle and conventional macro contacts. We determined which signal modality is the most capable of decoding speech production, and tested if the combination of these signals could improve the decoding accuracy of spoken phonemes. Feature vectors were constructed from spike frequency obtained from SUAs and event-related spectral perturbation derived from ECoG and LFP signals, then input to the decoder. The results showed that the decoding accuracy for five spoken vowels was highest when features from multiple signals were combined and optimized for each subject, and reached 59% when averaged across all six subjects. This result suggests that multi-scale signals convey complementary information for speech articulation. The current study demonstrated that simultaneous recording of multi-scale neuronal activities could raise decoding accuracy even though the recording area is limited to a small portion of cortex, which is advantageous for future implementation of speech-assisting BCIs.
Klebsiella variicola,
a member of
K. pneumoniae
phylogroup, can cause severe infectious diseases. We report a case of
K. variicola
meningitis after neurosurgery. The bacterium was isolated from blood and cerebrospinal fluid, and bacterial species identification was carried out by using both matrix-assisted laser-desorption/ionization time-of-flight mass spectroscopy (MALDI-TOF MS) and whole genome sequencing. Initially, the organism was misidentified as
K. pneumoniae
by VITEK®2; automated system in the clinical laboratory examination. The patient recovered with the combination of surgical drainage and antimicrobial treatment. To our knowledge, this is the first case report of post-surgical meningitis caused by
K. variicola.
As experienced in this case, the automated bacterial identification system popularly being used in the clinical laboratory might not be effective enough for bacterial species identification. The use of MALDI-TOF MS for microbial identification may be helpful to physicians for appropriate management of
K. pneumoniae
phylogroup infection.
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