Identification and Connectomic Profiling of Concussion Using Bayesian Machine Learning.

Accurate early diagnosis of concussion is useful to prevent sequelae and improve neurocognitive outcomes. Early after head impact, concussion diagnosis may be doubtful in persons whose neurological, neuroradiological, and/or neurocognitive examinations are equivocal. Such individuals can benefit from novel accurate assessments that complement clinical diagnostics. We introduce a Bayesian machine learning classifier to identify concussion through cortico-cortical connectome mapping from magnetic resonance imaging in persons with quasi-normal cognition and without neuroradiological findings. Classifier features are generated from connectivity matrices specifying the mean fractional anisotropy of white matter connections linking brain structures. Each connection's saliency to classification was quantified by training individual classifier instantiations using a single feature type. The classifier was tested on a discovery sample of 92 healthy controls (HCs; 26 females, age µ ± σ: 39.8 ± 15.5 years) and 471 adult mTBI patients (158 females, age µ ± σ: 38.4 ± 5.9 years). Results were replicated in an independent validation sample of 256 HCs (149 females, age µ ± σ: 55.3 ± 12.1 years) and 126 patients with concussion (46 females, age µ ± σ: 39.0 ± 17.7 years). Classifier accuracy exceeds 99% in both samples, suggesting robust generalizability to new samples. Notably, 13 bilateral cortico-cortical connection pairs predict diagnostic status with accuracy exceeding 99% in both discovery and validation samples. Many such connection pairs are between prefrontal cortex structures, fronto-limbic and fronto-subcortical structures, and occipito-temporal structures in the ventral ("what") visual stream. This and related connectivity form a highly salient network of brain connections that is particularly vulnerable to concussion. Because these connections are important in mediating cognitive control, memory, and attention, our findings explain the high frequency of cognitive disturbances after concussion. Our classifier was trained and validated on concussed participants with cognitive profiles very similar to those of HCs. This suggests that the classifier can complement current diagnostics by providing independent information in clinical contexts where patients have quasi-normal cognition but where concussion diagnosis stands to benefit from additional evidence.

Older age, male sex, and cerebral microbleeds predict white matter loss after traumatic brain injury.

Little is known on how mild traumatic brain injury affects white matter based on age at injury, sex, cerebral microbleeds, and time since injury. Here, we study the fractional anisotropy of white matter to study these effects in 109 participants aged 18-77 (46 females, age µ ± σ = 40 ± 17 years) imaged within [Formula: see text] 1 week and [Formula: see text] 6 months post-injury. Age is found to be linearly associated with white matter degradation, likely due not only to injury but also to cumulative effects of other pathologies and to their interactions with injury. Age is associated with mean anisotropy decreases in the corpus callosum, middle longitudinal fasciculi, inferior longitudinal and occipitofrontal fasciculi, and superficial frontal and temporal fasciculi. Over [Formula: see text] 6 months, the mean anisotropies of the corpus callosum, left superficial frontal fasciculi, and left corticospinal tract decrease significantly. Independently of other predictors, age and cerebral microbleeds contribute to anisotropy decrease in the callosal genu. Chronically, the white matter of commissural tracts, left superficial frontal fasciculi, and left corticospinal tract degrade appreciably, independently of other predictors. Our findings suggest that large commissural and intra-hemispheric structures are at high risk for post-traumatic degradation. This study identifies detailed neuroanatomic substrates consistent with brain injury patients' age-dependent deficits in information processing speed, interhemispheric communication, motor coordination, visual acuity, sensory integration, reading speed/comprehension, executive function, personality, and memory. We also identify neuroanatomic features underlying white matter degradation whose severity is associated with the male sex. Future studies should compare our findings to functional measures and other neurodegenerative processes.

Maturation of Social-Vocal Communication in Prairie Vole (Microtus ochrogaster) Pups.

Impairments in social communication are common among neurodevelopmental disorders. While traditional animal models have advanced our understanding of the physiological and pathological development of social behavior, they do not recapitulate some aspects where social communication is essential, such as biparental care and the ability to form long-lasting social bonds. Prairie voles (Microtus ochrogaster) have emerged as a valuable rodent model in social neuroscience because they naturally display these behaviors. Nonetheless, the role of vocalizations in prairie vole social communication remains unclear. Here, we studied the ontogeny [from postnatal days (P) 8-16] of prairie vole pup ultrasonic vocalizations (USVs), both when isolated and when the mother was present but physically unattainable. In contrast to other similarly sized rodents such as mice, prairie vole pups of all ages produced isolation USVs with a relatively low fundamental frequency between 22 and 50 kHz, often with strong harmonic structure. Males consistently emitted vocalizations with a lower frequency than females. With age, pups vocalized less, and the acoustic features of vocalizations (e.g., duration and bandwidth) became more stereotyped. Manipulating an isolated pup's social environment by introducing its mother significantly increased vocal production at older (P12-16) but not younger ages, when pups were likely unable to hear or see her. Our data provide the first indication of a maturation in social context-dependent vocal emission, which may facilitate more active acoustic communication. These results help lay a foundation for the use of prairie voles as a model organism to probe the role of early life experience in the development of social-vocal communication.