Publications by authors named "Aydin Alikaya"

Background: High-precision neurosurgical targeting in nonhuman primates (NHPs) often requires presurgical anatomical mapping with noninvasive neuroimaging techniques (MRI, CT, PET), allowing for translation of individual anatomical coordinates to surgical stereotaxic apparatus. Given the varied tissue contrasts that these imaging techniques produce, precise alignment of imaging-based coordinates to surgical apparatus can be cumbersome. MRI-compatible stereotaxis with radiopaque fiducial markers offer a straight-forward and reliable solution, but existing commercial options do not fit in conformal head coils that maximize imaging quality.

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The common marmoset monkey (Callithrix jacchus) is a species of rising prominence in the neurosciences due to its small size, ease of handling, fast breeding, and its shared functional and structural brain characteristics with Old World primates. With increasing attention on modeling human brain diseases in marmosets, understanding how to deliver therapeutic or neurotropic agents to the marmoset brain noninvasively is of great preclinical importance. In other species, including humans, transcranial focused ultrasound (tFUS) aided by intravenously injected microbubbles has proven to be a transient, reliable, and safe method for disrupting the blood-brain barrier (BBB), allowing the focal passage of therapeutic agents that do not otherwise readily traverse the tight endothelial junctions of the BBB.

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Medium spiny neurons (MSNs) constitute the vast majority of striatal neurons and the principal interface between dopamine reward signals and functionally diverse cortico-basal ganglia circuits. Information processing in these circuits is dependent on distinct MSN types: cell types that are traditionally defined according to their projection targets or dopamine receptor expression. Single-cell transcriptional studies have revealed greater MSN heterogeneity than predicted by traditional circuit models, but the transcriptional landscape in the primate striatum remains unknown.

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Dopamine prediction error responses are essential components of universal learning mechanisms. However, it is unknown whether individual dopamine neurons reflect the shape of reward distributions. Here, we used symmetrical distributions with differently weighted tails to investigate how the frequency of rewards and reward prediction errors influence dopamine signals.

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Rewards are fundamental to everyday life. They confer pleasure, support learning, and mediate decisions. Dopamine-releasing neurons in the midbrain are critical for reward processing.

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