Anterior Auditory Field Is Needed for Sound Categorization in Fear Conditioning Task of Adult Rat

Biomaterials and bioelectronics for self-powered neurostimulation

Self-powered neurostimulation via biomaterials and bioelectronics innovation has emerged as a compelling approach to explore, repair, and modulate neural systems. This review examines the application of self-powered bioelectronics for electrical stimulation of both the central and peripheral nervous systems, as well as isolated neurons. Contemporary research has adeptly harnessed biomechanical and biochemical energy from the human body, through various mechanisms such as triboelectricity, piezoelectricity, magnetoelasticity, and biofuel cells, to power these advanced bioelectronics. Notably, these self-powered bioelectronics hold substantial potential for delivering neural stimulations that are customized for the treatment of neurological diseases, facilitation of neural regeneration, and the development of neuroprosthetics. Looking ahead, we expect that the ongoing advancements in biomaterials and bioelectronics will drive the field of self-powered neurostimulation toward the realization of more advanced, closed-loop therapeutic solutions, paving the way for personalized and adaptable neurostimulators in the coming decades.

Corticostriatal Neurons in the Anterior Auditory Field Regulate Frequency Discrimination Behavior

The anterior auditory field (AAF) is a core region of the auditory cortex and plays a vital role in discrimination tasks. However, the role of the AAF corticostriatal neurons in frequency discrimination remains unclear. Here, we used c-Fos staining, fiber photometry recording, and pharmacogenetic manipulation to investigate the function of the AAF corticostriatal neurons in a frequency discrimination task. c-Fos staining and fiber photometry recording revealed that the activity of AAF pyramidal neurons was significantly elevated during the frequency discrimination task. Pharmacogenetic inhibition of AAF pyramidal neurons significantly impaired frequency discrimination. In addition, histological results revealed that AAF pyramidal neurons send strong projections to the striatum. Moreover, pharmacogenetic suppression of the striatal projections from pyramidal neurons in the AAF significantly disrupted the frequency discrimination. Collectively, our findings show that AAF pyramidal neurons, particularly the AAF-striatum projections, play a crucial role in frequency discrimination behavior.

Non-Invasive Hybrid Ultrasound Stimulation of Visual Cortex In Vivo

The optic nerve is the second cranial nerve (CN II) that connects and transmits visual information between the retina and the brain. Severe damage to the optic nerve often leads to distorted vision, vision loss, and even blindness. Such damage can be caused by various types of degenerative diseases, such as glaucoma and traumatic optic neuropathy, and result in an impaired visual pathway. To date, researchers have not found a viable therapeutic method to restore the impaired visual pathway; however, in this paper, a newly synthesized model is proposed to bypass the damaged portion of the visual pathway and set up a direct connection between a stimulated visual input and the visual cortex (VC) using Low-frequency Ring-transducer Ultrasound Stimulation (LRUS). In this study, by utilizing and integrating various advanced ultrasonic and neurological technologies, the following advantages are achieved by the proposed LRUS model: 1. This is a non-invasive procedure that uses enhanced sound field intensity to overcome the loss of ultrasound signal due to the blockage of the skull. 2. The simulated visual signal generated by LRUS in the visual-cortex-elicited neuronal response in the visual cortex is comparable to light stimulation of the retina. The result was confirmed by a combination of real-time electrophysiology and fiber photometry. 3. VC showed a faster response rate under LRUS than light stimulation through the retina. These results suggest a potential non-invasive therapeutic method for restoring vision in optic-nerve-impaired patients using ultrasound stimulation (US).

Vowel speech recognition from rat electroencephalography using long short-term memory neural network

Over the years, considerable research has been conducted to investigate the mechanisms of speech perception and recognition. Electroencephalography (EEG) is a powerful tool for identifying brain activity; therefore, it has been widely used to determine the neural basis of speech recognition. In particular, for the classification of speech recognition, deep learning-based approaches are in the spotlight because they can automatically learn and extract representative features through end-to-end learning. This study aimed to identify particular components that are potentially related to phoneme representation in the rat brain and to discriminate brain activity for each vowel stimulus on a single-trial basis using a bidirectional long short-term memory (BiLSTM) network and classical machine learning methods. Nineteen male Sprague-Dawley rats subjected to microelectrode implantation surgery to record EEG signals from the bilateral anterior auditory fields were used. Five different vowel speech stimuli were chosen, /a/, /e/, /i/, /o/, and /u/, which have highly different formant frequencies. EEG recorded under randomly given vowel stimuli was minimally preprocessed and normalized by a z-score transformation to be used as input for the classification of speech recognition. The BiLSTM network showed the best performance among the classifiers by achieving an overall accuracy, f1-score, and Cohen’s κ values of 75.18%, 0.75, and 0.68, respectively, using a 10-fold cross-validation approach. These results indicate that LSTM layers can effectively model sequential data, such as EEG; hence, informative features can be derived through BiLSTM trained with end-to-end learning without any additional hand-crafted feature extraction methods.

The posterior auditory field is the chief generator of prediction error signals in the auditory cortex

The auditory cortex (AC) encompasses distinct fields subserving partly different aspects of sound processing. One essential function of the AC is the detection of unpredicted sounds, as revealed by differential neural activity to predictable and unpredictable sounds. According to the predictive coding framework, this effect can be explained by repetition suppression and/or prediction error signaling. The present study investigates functional specialization of the rat AC fields in repetition suppression and prediction error by combining a tone frequency oddball paradigm (involving high-probable standard and low-probable deviant tones) with two different control sequences (many-standards and cascade). Tones in the control sequences were comparable to deviant events with respect to neural adaptation but were not violating a regularity. Therefore, a difference in the neural activity between deviant and control tones indicates a prediction error effect, whereas a difference between control and standard tones indicates a repetition suppression effect. Single-unit recordings revealed by far the largest prediction error effects for the posterior auditory field, while the primary auditory cortex, the anterior auditory field, the ventral auditory field, and the suprarhinal auditory field were dominated by repetition suppression effects. Statistically significant repetition suppression effects occurred in all AC fields, whereas prediction error effects were less robust in the primary auditory cortex and the anterior auditory field. Results indicate that the non-lemniscal, posterior auditory field is more engaged in context-dependent processing underlying deviance-detection than the other AC fields, which are more sensitive to stimulus-dependent effects underlying differential degrees of neural adaptation.

Neuroplastic changes in auditory cortex induced by long-duration "non-traumatic" noise exposures are triggered by deficits in the neural output of the cochlea

Long-term exposure to moderate intensity noise that does not cause measureable hearing loss can cause striking changes in sound-evoked neural activity in auditory cortex.  It is unclear if these changes originate in the cortex or result from functional deficits in the neural output of the cochlea.  To explore this issue, rats were exposed for 6-weeks to 18-24 kHz noise at 45, 65 or 85 dB SPL and then compared the noise-induced changes in the cochlear compound action potential (CAP) with the neurophysiological alterations in the anterior auditory field (AAF) of auditory cortex. The 45-dB exposure, which had no effect on the cochlear CAP also had no effect on the AAF. In contrast, the 85-dB exposure greatly reduced CAP amplitudes at high frequencies, but had little or no effect on low frequencies. Despite the large reduction in high-frequency CAP neural responses, high frequency AAF neural responses (spike rate and local field potential amplitude) remained largely within normal limits, evidence of central gain compensation. AAF responses were also enhanced at the low frequencies even though CAP responses were normal; this AAF hyperactivity only occurred at low-moderate intensities (level-dependent enhanced central gain). The 65-dB exposure also caused a moderate reduction in high-frequency CAP amplitudes. Notwithstanding this cochlear loss, AAF responses were boosted into the normal range, evidence of homeostatic gain compensation. Our results suggest that the noise-induced neuroplastic changes in the auditory cortex from so-called "non-traumatic" exposures are triggered from functional deficits in the neural output of the cochlea.

Adaptation in the Dorsal Belt and Core Regions of the Auditory Cortex in the Awake Rat

The rat auditory cortex is divided anatomically into several areas, but little is known about the functional differences in information processing among these areas. Three tonotopically organized core fields, namely, the primary (A1), anterior (AAF), and ventral (VAF) auditory fields, as well as one non-tonotopically organized belt field, the dorsal belt (DB), were identified based on their response properties. Compared to neurons in A1, AAF and VAF, units in the DB exhibited little or no response to pure tones but strong responses to white noise. The few DB neurons responded to pure tones with thresholds greater than 60 dB SPL, which was significantly higher than the thresholds of neurons in the core regions. In response to white noise, units in DB showed significantly longer latency and lower peak response, as well as longer response duration, than those in the core regions. Responses to repeated white noise were also examined. In contrast to neurons in A1, AAF and VAF, DB neurons could not follow repeated stimulation at a 300 ms inter-stimulus interval (ISI) and showed a significant steeper ISI tuning curve slope when the ISI was increased from 300 ms to 4.8 s. These results indicate that the DB processes auditory information on broader spectral and longer temporal scales than the core regions, reflecting a distinct role in the hierarchical cortical pathway.