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Abdulkerim, M. E.

Publications and source records attributed to Abdulkerim, M. E..

2 recordsLinked to original sources

Oscillatory activity in alpha/beta frequencies coordinates auditory and prefrontal cortices during extinction learning

Cortical synchrony is theorized to contribute to communication between connected networks during executive functioning. To understand the functional role of neural synchrony in cognitive flexibility, we recorded from auditory cortex (AC) and medial prefrontal cortex (mPFC), while mice performed an auditory extinction learning task. We found that while animals gradually showed reduced responding to the unrewarded tone over hundreds of trials, the power of local field potential (LFP) oscillations (8-18 Hz, centered at alpha/beta frequencies) in AC and mPFC exhibited immediate and robust increases, prior to behavioral changes. The strength of LFP alpha/beta power in the mPFC, but not AC, was strongly correlated with the behavioral performance that mice would achieve later in the training session. Further, we found that coherence between AC and mPFC at 8-18Hz was selectively enhanced only after mice learned to suppress licking, and this LFP coherence increase coincided with a reduction in spiking rate for the unrewarded tone in AC. These results reveal that enhanced interactions between PFC and AC is an inherent property of auditory discrimination learning, and that coordinated alpha/beta oscillations contribute to cognitive flexibility.

neuroscience↗

Distinct Neuronal Populations Contribute to Trace Conditioning and Extinction Learning in the Hippocampal CA1

Trace conditioning and extinction learning depend on the hippocampus, but it remains unclear how ongoing neural activities in the hippocampus are modulated during different learning processes. To explore this question, we performed calcium imaging in a large number of individual CA1 neurons during both trace eye-blink conditioning and subsequent extinction learning in mice. Using trial-averaged calcium fluorescence analysis, we found direct evidence that in real time, as learning emerges, distinct populations of CA1 cells contribute to trace conditioned learning versus extinction learning. Furthermore, we examined network connectivity by calculating co-activity between CA1 neuron pairs, and found that CA1 network connectivity is different between conditioning and extinction and between correct versus incorrect behavioral responses during trace conditioned learning. However, the overall connectivity density remains constant across these behavioral conditions. Together, our results demonstrate that distinct populations of CA1 neurons, forming different sub-networks with unique connectivity patterns, encode different aspects of learning.

neuroscience↗