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Brain Reserve The term brain reserve reflects structural properties of the brain such as brain volume (Bigler et al., 2006), cerebral metabolism (Cohen et al, 1999), lesion loads (Cader et al., 2006) and patterns of  structural connectivity (Alstott et al., 2009; Becker et al., 2016). Depending on their amount of 'reserve', different people show different abilities to compensate for, or cope with, brain pathology. 'Brain reserve' refers to the structural elements that mediate one's resilience to pathology/injury. Thus, the Brain Reserve hypothesis is a passive-quantitative model which ascribes different level of resilience to variables such as brain volume and synapse count. The Cognitive Reserve hypothesis, instead, suggests that the brain actively attempts to cope with damage by using pre-existing cognitive processes or enlisting compensatory strategies. Cognitive reserve includes the ability to recruit networks, so a high CR entails more efficient plasticity. In this sense, CR represents the active side of one's 'reserve' and describes the resilience of the mind (functional), as opposed to that of the brain (structural). However, BR and CR can not be considered as distinct and independent. In fact, CR needs to be implemented at a neural level.. AS Stern (2) explicitly suggested, there is neural implementation of CR in terms of efficiency, capacity and flexibility of synaptic reorganization, and in terms of the relative utilization of specific brain regions. Similarly, intensive cognitive stimulation may be associated with increased brain volume in childhood (e.g., 8) Each person presents individual variability in the structural integrity of the nervous system, influencing their functional and  behavioral abilities after the onset of a neuropathology. Indeed, people with less brain reserve are thought to have lower threshold for the expression of functional impairments after brain insults. In this way, brain reserve influences the observable clinical sequelae (Medaglia et al., 2018). The concept of brain reserve capacity (BRC), defined through indexes such as brain size and total synapse count and described in the threshold model (Satz, 1993), was conceived to explain how  individual differences in the BRC could account for different clinical symptoms. Once a certain threshold of brain reserve is depleted, then clinical symptoms become observable. If two patients have different amounts of BRC, a brain lesion may go beyond the threshold level for a patient and  let clinical symptoms show up, while the same damage may not reach the threshold for the other  patient, who will not present observable deficits. Then, higher amounts of brain reserve are a factor of resilience against brain insults such as lesions, neurodegenerative diseases and aging  processing (Stern, 2002). Example of brain reserve as a predictor of clinical symptoms following neurodegenerative diseases comes from studies on Alzheimer’s population (Mori et al., 1997) where patients’ premorbid higher  amount of brain volume was found to be associated with later onset of clinical symptoms from the  pathology (Schofield et al., 1995). Early references to brain reserve came by Katzman et al. in 1988, who noted that individuals with high levels of Alzheimer’s disease pathology post mortem who otherwise remained nondemented  in life had higher-than-average weight of their brains, and in particular, almost double the number of large pyramidal neurons throughout their neocortex in  comparison with those who expressed clinical symptoms (Valenzuela, 2008). Nevertheless, brain reserve remains a “passive” form of capacity to face brain insults (Medaglia et al., 2018).

Cognitive Reserve Index questionnaire (CRIq): a new instrument for measuring cognitive reserve Aging Clinical and Experimental Research Massimo Nucci1, Daniela Mapelli1,2 and Sara Mondini1

One of the major concerns about brain reserve is operationalizing it. New lines of evidence (Honey et al., 2009; Honey et al., 2010; Medaglia et al., 2015; Wen et al., 2011) suggest that the  employment of advanced network analysis could provide more accurate measures of the relation  between structural and functional brain properties, as opposite to traditionally measured variables  (e.g., whole brain volume, cerebral metabolism) (Medaglia et al., 2018). Indeed, understanding brain reserve is crucial to uncover neurophysiological mechanisms that link brain morphology and  function to clinical outcomes. A proposed mechanism of reserve is brain plasticity (Fratiglioni, 2007), which promotes changes that may contribute to both brain and cognitive resilience.