Pathological slow-wave activity and impaired working memory binding in post-traumatic amnesia

Associative binding is key to normal memory function and is transiently disrupted during periods of post-traumatic amnesia (PTA) following traumatic brain injury (TBI). Electrophysiological abnormalities including low-frequency activity are common following TBI. Here, we investigate associative memory binding during PTA and test the hypothesis that misbinding is caused by pathological slowing of brain activity disrupting cortical communication. Thirty acute moderate-severe TBI patients (25 males; 5 females) and 26 healthy controls (20 males; 6 females) were tested with a precision working memory paradigm requiring the association of object and location information. Electrophysiological effects of TBI were assessed using resting-state EEG in a subsample of 17 patients and 21 controls. PTA patients showed abnormalities in working memory function and made significantly more misbinding errors than patients who were not in PTA and controls. The distribution of localisation responses was abnormally biased by the locations of non-target items for patients in PTA suggesting a specific impairment of object and location binding. Slow wave activity was increased following TBI. Increases in the delta-alpha ratio indicative of an increase in low-frequency power specifically correlated with binding impairment in working memory. Connectivity changes in TBI did not correlate with binding impairment. Working memory and electrophysiological abnormalities normalised at six-month follow-up. These results show that patients in PTA show high rates of misbinding that are associated with a pathological shift towards lower frequency oscillations

Traumatic brain injury: a comparison of diffusion and volumetric magnetic resonance imaging measures

Cognitive impairment after traumatic brain injury remains hard to predict. This is partly because axonal injury, which is of fundamental importance, is difficult to measure clinically. Advances in MRI allow axonal injury to be detected after traumatic brain injury, but the most sensitive approach is unclear. Here, we compare the performance of diffusion tensor imaging, neurite orientation dispersion and density-imaging and volumetric measures of brain atrophy in the identification of white-matter abnormalities after traumatic brain injury. Thirty patients with moderate-severe traumatic brain injury in the chronic phase and 20 age-matched controls had T1-weighted and diffusion MRI. Neuropsychological tests of processing speed, executive functioning and memory were used to detect cognitive impairment. Extensive abnormalities in neurite density index and orientation dispersion index were observed, with distinct spatial patterns. Fractional anisotropy and mean diffusivity also indicated widespread abnormalities of white-matter structure. Neurite density index was significantly correlated with processing speed. Slower processing speed was also related to higher mean diffusivity in the corticospinal tracts. Lower white-matter volumes were seen after brain injury with greater effect sizes compared to diffusion metrics; however, volume was not sensitive to changes in cognitive performance. Volume was the most sensitive at detecting change between groups but was not specific for determining relationships with cognition. Abnormalities in fractional anisotropy and mean diffusivity were the most sensitive diffusion measures; however, neurite density index and orientation dispersion index may be more spatially specific. Lower neurite density index may be a useful metric for examining slower processing speed

Abnormal dorsal attention network activation in memory impairment after traumatic brain injury

Memory impairment is a common, disabling effect of traumatic brain injury. In healthy individuals, successful memory encoding is associated with activation of the dorsal attention network as well as suppression of the default mode network. Here, in traumatic brain injurypatients we examined whether: i) impairments in memory encoding are associated with abnormal brain activation in these networks; ii) whether changes in this brain activity predict subsequent memory retrieval; and iii) whether abnormal white matter integrity underpinningfunctional networks is associated with impaired subsequent memory. 35 patients with moderate-severetraumatic brain injury aged 23-65 years (74% males) in the post-acute/chronic phase after injury and 16 healthy controls underwent functional MRI during performance of an abstract image memory encoding task. Diffusion tensor imaging was used to assess structural abnormalities across patient groups compared to 28 age-matched healthy controls. Successful memory encoding across all participants was associated with activation of the dorsal attention network, the ventral visual stream and medial temporal lobes. Decreased activation was seen in the default mode network. Patients with preserved episodic memory demonstrated increased activation in areas of the dorsal attention network.Patients with impaired memory showed increased left anterior prefrontal activity. White matter microstructure underpinning connectivity between core nodes of the encoding networks was significantly reduced in patients with memory impairment. Our results show for the first time that patients with impaired episodic memory show abnormal activation of key nodes within the dorsal attention network and regions regulating default mode network activity during encoding. Successful encoding was associated with an opposite direction of signal change between patients with and without memory impairment, suggesting that memory encoding mechanisms could be fundamentally altered in this population. We demonstrate a clear relationship between functional networks activated during encoding and underlying abnormalities within the structural connectome in patients with memory impairment. We suggest that encoding failures in this group are likely due to failed control of goal-directed attentional resources

The impact of CACNA1C gene, and its epistasis with ZNF804A, on white matter microstructure in health, schizophrenia and bipolar disorder

Genome-wide studies have identified allele A (adenine) of single nucleotide polymorphism (SNP) rs1006737 of the calcium-channel CACNA1C gene as a risk factor for both schizophrenia (SZ) and bipolar disorder (BD) as well as allele A for rs1344706 in the zinc-finger ZNF804A gene. These illnesses have also been associated with white matter abnormalities, reflected by reductions in fractional anisotropy (FA), measured using diffusion tensor imaging (DTI). We assessed the impact of the CACNA1C psychosis risk variant on FA in SZ, BD and health. 230 individuals (with existing ZNF804A rs1344706 genotype data) were genotyped for CACNA1C rs1006737 and underwent DTI. FA data was analysed with tract-based spatial statistics and threshold-free cluster enhancement significance correction (p < 0.05) to detect effects of CACNA1C genotype on FA, and its potential interaction with ZNF804A genotype and with diagnosis, on FA. There was no significant main effect of the CACNA1C genotype on FA, nor diagnosis by genotype(s) interactions. Nevertheless, when inspecting SZ in particular, risk allele carriers had significantly lower FA than the protective genotype individuals, in portions of the left middle occipital and parahippocampal gyri, right cerebelleum, left optic radiation and left inferior and superior temporal gyri. Our data suggests a minor involvement of CACNA1C rs1006737 in psychosis via conferring susceptibility to white matter microstructural abnormalities in SZ. Put in perspective, ZNF804A rs1344706, not only had a significant main effect, but its SZ-specific effects were two orders of magnitude more widespread than that of CACNA1C rs1006737

Axonal marker neurofilament light predicts long-term outcomes and progressive neurodegeneration after traumatic brain injury

Axonal injury is a key determinant of long-term outcomes after traumatic brain injury (TBI) but has been difficult to measure clinically. Fluid biomarker assays can now sensitively quantify neuronal proteins in blood. Axonal components such as neurofilament light (NfL) potentially provide a diagnostic measure of injury. In the multicenter BIO-AX-TBI study of moderate-severe TBI, we investigated relationships between fluid biomarkers, advanced neuroimaging, and clinical outcomes. Cerebral microdialysis was used to assess biomarker concentrations in brain extracellular fluid aligned with plasma measurement. An experimental injury model was used to validate biomarkers against histopathology. Plasma NfL increased after TBI, peaking at 10 days to 6 weeks but remaining abnormal at 1 year. Concentrations were around 10 times higher early after TBI than in controls (patients with extracranial injuries). NfL concentrations correlated with diffusion MRI measures of axonal injury and predicted white matter neurodegeneration. Plasma TAU predicted early gray matter atrophy. NfL was the strongest predictor of functional outcomes at 1 year. Cerebral microdialysis showed that NfL concentrations in plasma and brain extracellular fluid were highly correlated. An experimental injury model confirmed a dose-response relationship of histopathologically defined axonal injury to plasma NfL. In conclusion, plasma NfL provides a sensitive and clinically meaningful measure of axonal injury produced by TBI. This reflects the extent of underlying damage, validated using advanced MRI, cerebral microdialysis, and an experimental model. The results support the incorporation of NfL sampling subacutely after injury into clinical practice to assist with the diagnosis of axonal injury and to improve prognostication

The sub-seasonal to seasonal prediction (S2S) project database

A database containing sub-seasonal to seasonal forecasts from 11 operational centres is available to the research community and will help advance our understanding of the sub-seasonal to seasonal time range. Demands are growing rapidly in the operational prediction and applications communities for forecasts that fill the gap between medium-range weather and long-range or seasonal forecasts. Based on the potential for improved forecast skill at the sub-seasonal to seasonal time range, a sub-seasonal prediction (S2S) research project has been established by the World Weather Research Program/World Climate Research Program. A main deliverable of this project is the establishment of an extensive database, containing sub-seasonal (up to 60 days) forecasts, 3-weeks behind real-time, and reforecasts from 11 operational centers, modelled in part on the THORPEX Interactive Grand Global Ensemble (TIGGE) database for medium range forecasts (up to 15 days). The S2S database, available to the research community since May 2015, represents an important tool to advance our understanding of the sub-seasonal to seasonal time range that has been considered for a long time as a “desert of predictability”. In particular, this database will help identify common successes and shortcomings in the model simulation and prediction of sources of sub-seasonal to seasonal predictability. For instance, a preliminary study suggests that the S2S models underestimate significantly the amplitude of the Madden Julian Oscillation (MJO) teleconnections over the Euro-Atlantic sector. The S2S database represents also an important tool for case studies of extreme events. For instance, a multi-model combination of S2S models displays higher probability of a landfall over Vanuatu islands 2 to 3 weeks before tropical cyclone Pam devastated the islands in March 2015