Object category learning is a fundamental ability, requiring the combination of "bottom-up" stimulus-driven with "top-down" task-specific information. It therefore may be a fruitful domain for study of the general neural mechanisms underlying cortical plasticity. A simple model predicts that category learning involves the formation of a task-independent shape-selective representation that provides input to circuits learning the categorization task, with the computationally appealing prediction of facilitated learning of additional, novel tasks over the same stimuli. Using fMRI rapid-adaptation techniques, we find that categorization training (on morphed "cars") induced a significant release from adaptation for small shape changes in lateral occipital cortex irrespective of category membership, compatible with the sharpening of a representation coding for physical appearance. In contrast, an area in lateral prefrontal cortex, selectively activated during categorization, showed sensitivity posttraining to explicit changes in category membership. Further supporting the model, categorization training also improved discrimination performance on the trained stimuli.

Summary Theories of reading have posited the existence of a neural representation coding for whole real words (i.e. an orthographic lexicon), but experimental support for such a representation has proved elusive. Using fMRI rapid adaptation techniques, we provide evidence that the human left ventral occipitotemporal cortex (specifically the “visual word form area”, VWFA) contains a representation based on neurons highly selective for individual real words, in contrast to current theories that posit a sublexical representation in the VWFA.

Understanding the neural mechanisms underlying object recognition is one of the fundamental challenges of visual neuroscience. While neurophysiology experiments have provided evidence for a "simple-to-complex" processing model based on a hierarchy of increasingly complex image features, behavioral and fMRI studies of face processing have been interpreted as incompatible with this account. We present a neurophysiologically plausible, feature-based model that quantitatively accounts for face discrimination characteristics, including face inversion and "configural" effects. The model predicts that face discrimination is based on a sparse representation of units selective for face shapes, without the need to postulate additional, "face-specific" mechanisms. We derive and test predictions that quantitatively link model FFA face neuron tuning, neural adaptation measured in an fMRI rapid adaptation paradigm, and face discrimination performance. The experimental data are in excellent agreement with the model prediction that discrimination performance should asymptote as faces become dissimilar enough to activate different neuronal populations.

The nature of orthographic representations in the human brain is still subject of much debate. Recent reports have claimed that the visual word form area (VWFA) in left occipitotemporal cortex contains an orthographic lexicon based on neuronal representations highly selective for individual written real words (RWs). This theory predicts that learning novel words should selectively increase neural specificity for these words in the VWFA. We trained subjects to recognize novel pseudowords (PWs) and used fMRI rapid adaptation to compare neural selectivity with RWs, untrained PWs (UTPWs), and trained PWs (TPWs). Before training, PWs elicited broadly tuned responses, whereas responses to RWs indicated tight tuning. After training, TPW responses resembled those of RWs, whereas UTPWs continued to show broad tuning. This change in selectivity was specific to the VWFA. Therefore, word learning appears to selectively increase neuronal specificity for the new words in the VWFA, thereby adding these words to the brain's visual dictionary.

Debates about motor theories of speech perception have recently been reignited by a burst of reports implicating premotor cortex (PMC) in speech perception. Often, however, these debates conflate perceptual and decision processes. Evidence that PMC activity correlates with task difficulty and subject performance suggests that PMC might be recruited, in certain cases, to facilitate category judgments about speech sounds (rather than speech perception, which involves decoding of sounds). However, it remains unclear whether PMC does, indeed, exhibit neural selectivity that is relevant for speech decisions. Further, it is unknown whether PMC activity in such cases reflects input via the dorsal or ventral auditory pathway, and whether PMC processing of speech is automatic or task-dependent. In a novel modified categorization paradigm, we presented human subjects with paired speech sounds from a phonetic continuum but diverted their attention from phoneme category using a challenging dichotic listening task. Using fMRI rapid adaptation to probe neural selectivity, we observed acoustic-phonetic selectivity in left anterior and left posterior auditory cortical regions. Conversely, we observed phoneme-category selectivity in left PMC that correlated with explicit phoneme-categorization performance measured after scanning, suggesting that PMC recruitment can account for performance on phoneme-categorization tasks. Structural equation modeling revealed connectivity from posterior, but not anterior, auditory cortex to PMC, suggesting a dorsal route for auditory input to PMC. Our results provide evidence for an account of speech processing in which the dorsal stream mediates automatic sensorimotor integration of speech and may be recruited to support speech decision tasks.

Objective Preclinical evidence with nilotinib, a US Food and Drug Administration (FDA)‐approved drug for leukemia, indicates improvement in Alzheimer's disease phenotypes. We investigated whether nilotinib is safe, and detectable in cerebrospinal fluid, and alters biomarkers and clinical decline in Alzheimer's disease. Methods This single‐center, phase 2, randomized, double‐blind, placebo‐controlled study investigated the safety, tolerability, and pharmacokinetics of nilotinib, and measured biomarkers in participants with mild to moderate dementia due to Alzheimer's disease. The diagnosis was supported by cerebrospinal fluid or amyloid positron emission tomography biomarkers. Nilotinib 150 mg versus matching placebo was taken orally once daily for 26 weeks followed by nilotinib 300 mg versus placebo for another 26 weeks. Results Of the 37 individuals enrolled, 27 were women and the mean (SD) age was 70.7 (6.48) years. Nilotinib was well‐tolerated, although more adverse events, particularly mood swings, were noted with the 300 mg dose. In the nilotinib group, central nervous system (CNS) amyloid burden was significantly reduced in the frontal lobe compared to the placebo group. Cerebrospinal fluid Aβ40 was reduced at 6 months and Aβ42 was reduced at 12 months in the nilotinib group compared to the placebo. Hippocampal volume loss was attenuated (−27%) at 12 months and phospho‐tau‐181 was reduced at 6 months and 12 months in the nilotinib group. Interpretation Nilotinib is safe and achieves pharmacologically relevant cerebrospinal fluid concentrations. Biomarkers of disease were altered in response to nilotinib treatment. These data support a larger, longer, multicenter study to determine the safety and efficacy of nilotinib in Alzheimer's disease. ANN NEUROL 2020 ANN NEUROL 2020;88:183–194

The neural mechanisms underlying recovery of language after left hemisphere stroke remain elusive. Although older evidence suggested that right hemisphere language homologues compensate for damage in left hemisphere language areas, the current prevailing theory suggests that right hemisphere engagement is ineffective or even maladaptive. Using a novel combination of support vector regression-based lesion-symptom mapping and voxel-based morphometry, we aimed to determine whether local grey matter volume in the right hemisphere independently contributes to aphasia outcomes after chronic left hemisphere stroke. Thirty-two left hemisphere stroke survivors with aphasia underwent language assessment with the Western Aphasia Battery-Revised and tests of other cognitive domains. High-resolution T1-weighted images were obtained in aphasia patients and 30 demographically matched healthy controls. Support vector regression-based multivariate lesion-symptom mapping was used to identify critical language areas in the left hemisphere and then to quantify each stroke survivor's lesion burden in these areas. After controlling for these direct effects of the stroke on language, voxel-based morphometry was then used to determine whether local grey matter volumes in the right hemisphere explained additional variance in language outcomes. In brain areas in which grey matter volumes related to language outcomes, we then compared grey matter volumes in patients and healthy controls to assess post-stroke plasticity. Lesion-symptom mapping showed that specific left hemisphere regions related to different language abilities. After controlling for lesion burden in these areas, lesion size, and demographic factors, grey matter volumes in parts of the right temporoparietal cortex positively related to spontaneous speech, naming, and repetition scores. Examining whether domain general cognitive functions might explain these relationships, partial correlations demonstrated that grey matter volumes in these clusters related to verbal working memory capacity, but not other cognitive functions. Further, grey matter volumes in these areas were greater in stroke survivors than healthy control subjects. To confirm this result, 10 chronic left hemisphere stroke survivors with no history of aphasia were identified. Grey matter volumes in right temporoparietal clusters were greater in stroke survivors with aphasia compared to those without history of aphasia. These findings suggest that the grey matter structure of right hemisphere posterior dorsal stream language homologues independently contributes to language production abilities in chronic left hemisphere stroke, and that these areas may undergo hypertrophy after a stroke causing aphasia.

Reading has been shown to rely on a dorsal brain circuit involving the temporoparietal cortex (TPC) for grapheme-to-phoneme conversion of novel words (Pugh et al., 2001), and a ventral stream involving left occipitotemporal cortex (OTC) (in particular in the so-called “visual word form area”, VWFA) for visual identification of familiar words. In addition, portions of the inferior frontal cortex (IFC) have been posited to be an output of the dorsal reading pathway involved in phonology. While this dorsal versus ventral dichotomy for phonological and orthographic processing of words is widely accepted, it is not known if these brain areas are actually strictly sensitive to orthographic or phonological information. Using an fMRI rapid adaptation technique we probed the selectivity of the TPC, OTC, and IFC to orthographic and phonological features during single word reading. We found in two independent experiments using different task conditions in adult normal readers, that the TPC is exclusively sensitive to phonology and the VWFA in the OTC is exclusively sensitive to orthography. The dorsal IFC (BA 44), however, showed orthographic but not phonological selectivity. These results support the theory that reading involves a specific phonological-based temporoparietal region and a specific orthographic-based ventral occipitotemporal region. The dorsal IFC, however, was not sensitive to phonological processing, suggesting a more complex role for this region.