The division of human learning systems into reward and punishment opponent modules is still a debated issue. While the implication of ventral prefrontostriatal circuits in reward-based learning is well established, the neural underpinnings of punishment-based learning remain unclear. To elucidate the causal implication of brain regions that were related to punishment learning in a previous functional neuroimaging study, we tested the effects of brain damage on behavioral performance, using the same task contrasting monetary gains and losses. Cortical and subcortical candidate regions, the anterior insula and dorsal striatum, were assessed in patients presenting brain tumor and Huntington disease, respectively. Both groups exhibited selective impairment of punishment-based learning. Computational modeling suggested complementary roles for these structures: the anterior insula might be involved in learning the negative value of loss-predicting cues, whereas the dorsal striatum might be involved in choosing between those cues so as to avoid the worst.

Tapping deficits are evident throughout manifest and premanifest stages. Deficits are more pronounced in later stages and correlate with clinical scores as well as regional brain atrophy, which implies a link between structure and function. The ability to track motor phenotype progression with force-transducer-based tapping measures will be tested prospectively in the TRACK-HD study.

Background Spinocerebellar Ataxias (SCAs) belong to polyglutamine repeat disorders and are characterized by a predominant atrophy of the cerebellum and the pons. Methods Proton magnetic resonance spectroscopy (1H MRS) using an optimised semiadiabatic localization by adiabatic selective refocusing (semi-LASER) protocol was performed at 3 T to determine metabolite concentrations in the cerebellar vermis and pons of a cohort of patients with SCA1 (n = 16), SCA2 (n = 12), SCA3 (n = 21), SCA7 (n = 12) and healthy controls (n = 33). Results Compared to controls, patients displayed lower total N-acetylaspartate and, to a lesser extent, lower glutamate, reflecting neuronal loss/dysfunction, while the glial marker, myo-inositol, was elevated. Patients also showed higher total creatine as reported in Huntington disease, another polyglutamine repeat disorder. There was a strong correlation between the Scale for the Assessment and Rating of Ataxia and the neurometabolites in both affected regions of patients. Principal component analyses confirmed that neuronal metabolites (total N-acetylaspartate and glutamate) were inversely correlated in the vermis and the pons to glial (myo-inositol) and energetic (total creatine) metabolites, as well as to disease severity (motor scales). Neurochemical plots with selected metabolites also allowed the separation of SCA2 and SCA3 from controls. Conclusion The neurometabolic profiles detected in patients underlie cell-specific changes in neuronal and astrocytic compartments that cannot be assessed by other neuroimaging modalities. The inverse correlation between metabolites from these two compartments suggests a metabolic attempt to compensate for neuronal damage in SCAs. Because these biomarkers reflect dynamic aspects of cellular metabolism, they are good candidates for proof-of-concept therapeutic trials.