Graph analysis of verbal fluency test discriminate between patients with Alzheimer’s disease, Mild Cognitive Impairment and normal elderly controls

Verbal fluency is the ability to produce a satisfying sequence of spoken words during a given time interval. The core of verbal fluency lies in the capacity to manage the executive aspects of language. The standard scores of the semantic verbal fluency test are broadly used in the neuropsychological assessment of the elderly, and different analytical methods are likely to extract even more information from the data generated in this test. Graph theory, a mathematical approach to analyze relations between items, represents a promising tool to understand a variety of neuropsychological states. This study reports a graph analysis of data generated by the semantic verbal fluency test by cognitively healthy elderly (NC), patients with Mild Cognitive Impairment – subtypes amnestic(aMCI) and amnestic multiple domain (a+mdMCI) - and patients with Alzheimer’s disease (AD). Sequences of words were represented as a speech graph in which every word corresponded to a node and temporal links between words were represented by directed edges. To characterize the structure of the data we calculated 13 speech graph attributes (SGAs). The individuals were compared when divided in three (NC – MCI – AD) and four (NC – aMCI – a+mdMCI – AD) groups. When the three groups were compared, significant differences were found in the standard measure of correct words produced, and three SGA: diameter, average shortest path, and network density. SGA sorted the elderly groups with good specificity and sensitivity. When the four groups were compared, the groups differed significantly in network density, except between the two MCI subtypes and NC and aMCI. The diameter of the network and the average shortest path were significantly different between the NC and AD, and between aMCI and AD. SGA sorted the elderly in their groups with good specificity and sensitivity, performing better than the standard score of the task. These findings provide support for a new methodological frame to assess the strength of semantic memory through the verbal fluency task, with potential to amplify the predictive power of this test. Graph analysis is likely to become clinically relevant in neurology and psychiatry, and may be particularly useful for the differential diagnosis of the elderly.

Neurobiology and clinical implications of lucid dreaming

Several lines of evidence converge to the idea that rapid eye movement sleep (REMS) is a good model to foster our understanding of psychosis. Both REMS and psychosis course with internally generated perceptions and lack of rational judgment, which is attributed to a hyperlimbic activity along with hypofrontality. Interestingly, some individuals can become aware of dreaming during REMS, a particular experience known as lucid dreaming (LD), whose neurobiological basis is still controversial. Since the frontal lobe plays a role in self-consciousness, working memory and attention, here we hypothesize that LD is associated with increased frontal activity during REMS. A possible way to test this hypothesis is to check whether transcranial magnetic or electric stimulation of the frontal region during REMS triggers LD. We further suggest that psychosis and LD are opposite phenomena: LD as a physiological awakening while dreaming due to frontal activity, and psychosis as a pathological intrusion of dream features during wake state due to hypofrontality. We further suggest that LD research may have three main clinical implications. First, LD could be important to the study of consciousness, including its pathologies and other altered states. Second, LD could be used as a therapy for recurrent nightmares, a common symptom of depression and post-traumatic stress disorder. Finally, LD may allow for motor imagery during dreaming with possible improvement of physical rehabilitation. In all, we believe that LD research may clarify multiple aspects of brain functioning in its physiological, altered and pathological states.