Search bioRxiv⌕ Search

Biology subjects

Rasheed, J.

Publications and source records attributed to Rasheed, J..

2 recordsLinked to original sources

Chronic stress does not induce behavioural signs of tinnitus or cochlear synaptopathy in Mongolian gerbils

Tinnitus is commonly associated with psychosocial stress. However, it is unclear whether stress alone is sufficient to induce neural alterations resulting in tinnitus. In this study, we investigated the causal role of stress in tinnitus generation by experimentally isolating stress exposure as the sole independent variable in a well-established Mongolian gerbil model. Animals were subjected to repeated, inescapable electric foot shocks over three weeks to create a chronic, repeated stress paradigm. Behavioural, endocrine and histological measures were combined to assess tinnitus perception, stress system activation and cochlear synaptopathy. Repeated stress exposure reliably activated the endocrine stress response, as indicated by transient increases in serum cortisol following specific stress sessions. Basal cortisol levels returned to baseline values after the stress period. Behavioural assessment using gap-prepulse inhibition of the acoustic startle reflex revealed only isolated cases of behavioural signs of tinnitus, which occurred at a frequency consistent with false-positive detection and were evenly distributed between stress-exposed and control animals. Histological analyses revealed that ribbon synapse counts were preserved across the cochlea, with no evidence of stress-induced synaptopathy. No systematic relationships were observed between endocrine activation, behavioural outcomes and the number of inner hair cell ribbon synapses. Taken together, these findings suggest that, in the absence of acoustic trauma, repeated chronic stress is not sufficient to induce tinnitus or inner hair cell synaptopathy. These results argue against a primary causal role of stress alone in tinnitus generation and instead support models in which stress modulates symptom expression or perceptual salience in the context of pre-existing auditory dysfunction.

neuroscience↗

Deep learning based decoding of local field potential events

How is information processed in the cerebral cortex? To answer this question a lot of effort has been undertaken to create novel and to further develop existing neuroimaging techniques. Thus, a high spatial resolution of fMRI devices was the key to exactly localize cognitive processes. Furthermore, an increase in time-resolution and number of recording channels of electro-physiological setups has opened the door to investigate the exact timing of neural activity. However, in most cases the recorded signal is averaged over many (stimulus) repetitions, which erases the fine-structure of the neural signal. Here, we show that an unsupervised machine learning approach can be used to extract meaningful information from electro-physiological recordings on a single-trial base. We use an auto-encoder network to reduce the dimensions of single local field potential (LFP) events to create interpretable clusters of different neural activity patterns. Strikingly, certain LFP shapes correspond to latency differences in different recording channels. Hence, LFP shapes can be used to determine the direction of information flux in the cerebral cortex. Furthermore, after clustering, we decoded the cluster centroids to reverse-engineer the underlying prototypical LFP event shapes. To evaluate our approach, we applied it to both neural extra-cellular recordings in rodents, and intra-cranial EEG recordings in humans. Finally, we find that single channel LFP event shapes during spontaneous activity sample from the realm of possible stimulus evoked event shapes. A finding which so far has only been demonstrated for multi-channel population coding.

neuroscience↗