Tobias A. Mattei

Unveiling complexity: non-linear and fractal analysis in neuroscience and cognitive psychology

Although non-linear dynamics has been mastered by physicists and mathematicians for a long time, as most physical systems are inherently non-linear in nature (Kirillov and Dmitry, 2013), the more recent successful application of non-linear and fractal methods to modeling and prediction of several evolutionary, ecologic, genetic, and biochemical processes (Aviles, 1999) has generated great interest and enthusiasm for such type of approach among researchers in neuroscience and cognitive psychology. After initial works on this emerging field, it became clear that that multiple aspects of brain function as viewed from different perspectives and scales present a nonlinear behavior, with a complex phase space composed of multiple equilibrium points, limit cycles, stability regions, and trajectory flows as well as a dynamics which includes unstable periodic orbits, period-doubling bifurcations, as well as other features typical of chaotic systems (Birbaumer et al., 1995). Moreover it was also demonstrated that non-linear dynamics was able to explain several unique features of the brain such as plasticity and learning (Freeman, 1994). More recently the concept of strange attractors has lead to a new understanding of information processing in the brain which, instead of the old “localizationist” approaches (Wernicke, 1970), considers higher cognitive functions (such as language, attention, memory and decision-making) as systemic properties which emerge from the dynamic interaction between parallel streams of information flowing between highly interconnected neuronal clusters that are organized in a widely distributed circuit modulated by key central nodes (Mattei, 2013a,b). According to such paradigm, the concept of self-organization has been able to offer a proper account of the phenomenon of evolutionary emergence of new complex cognitive structures from non-deterministic random patterns, similarly to what has been previously observed in nonlinear studies of fluid dynamics (Dixon et al., 2012). Additionally, the challenges of interpreting massive amounts of information related to brain function generated from emerging research fields in experimental neuroscience (such as functional MRi, magnetoencephalography, optogenetics, and single-cell intra-operative recordings) have generated the necessity of new methods for which incorporate complex pattern analysis as an important feature of their algorithms (Turk-Browne, 2013). Up to now nonlinear methods have already been successfully employed to describe and model (among many other examples) single-cell firing patterns (Thomas et al., 2013), neural networks synchronization (Yu et al., 2011), autonomic activity (Tseng et al., 2013), electroencephalographic data (Abasolo et al., 2007), noise modulation in the cerebellum (Tokuda et al., 2010), as well as higher cognitive functions and complex psychiatric disorders (Bystritsky et al., 2012). Additionally fractal analysis has been extensively explored not only in the description of the temporal aspects of neuronal dynamics, but also in the evaluation of key structural patterns of cellular organization in both normal and pathological histologic brain samples (Mattei, 2013a,b). Finally, recent studies have demonstrated that several cognitive functions can be successfully modeled with basis on the transient activity of large-scale brain networks in the presence of noise (Rabinovich et al., 2008). In fact, it has already been suggested that the observed pervasiveness of the 1/f scaling (also called 1/f noise, fractal time, or pink noise) in both neural and cognitive functions may have a very close relationship (if not a causal one) with the phenomenon of metastability of brain states (Kello et al., 2008). Other studies in the emerging field of neuroeconomics have shown that it is possible to represent typical decision-making paradigms by dynamic models governed by ordinary differential equations with a finite number of possibilities at the decision points as well as basic rules to address uncertainty (Holmes et al., 2004). In this special edition of Frontiers Computational Neuroscience dedicated to the topic of Non-linear and Fractal Analysis in Neuroscience and Cognitive Psychology, special articles from several frontline research groups around the world were carefully selected in order to provide a representative sample of the different research fields in neuroscience and cognitive psychology where non-linear and fractal analysis may be successfully applied. The selected articles include both classical problems where non-linear method have been traditionally employed (such as EEG data analysis) as well as other new research fields in which non-linear analysis has been shown to be useful not only for modeling normal brain dynamics but also for the diagnosis of neurological and psychiatric disorders, monitoring of their natural history and evaluation of the effects of different therapeutic strategies. Overall, both theoretical and experimental works in the field seem to demonstrate that the advanced tools of non-linear analysis can much more accurately describe and represent the complexity of brain dynamics than traditional mathematical and computational methods based on linear and deterministic analysis. Although it seems quite unquestionable that future attempts to model complex brain and cognitive functions will significantly benefit from non-linear methods, the exact cognitive and neuronal variables that may exhibit a significant chaotic pattern is still an open question. However, taking into account the pervasiveness of non-linear behavior in the brain, which has already been demonstrated by such an extensive literature in so many different fields of neuroscience and cognitive psychology (as well as the remarkable progress that has been achieved by the application of non-linear and fractal analysis in such research areas), maybe the burden of proof should be on the other side. Perhaps the real question to be answered is: Which areas of neuroscience and cognitive psychology would not benefit from the advantages that non-linear and fractal analysis has to offer?

Redundans nervi radix cauda equina: pathophysiology and clinical significance of an intriguing radiologic sign.

he scenario is very simple and familiar to most neuro-surgeons: The magnetic resonance imaging (MRI) scan ofa patient with lumbar canal stenosis shows the nerves ofthe cauda equina in a tortuous, serpiginous, and tangledappearance above the site of constriction of the lumbar canal. Iremember being told in my early residency days to interpret sucha radiologic finding with the same concern for neural tissuecompression (and its associated deleterious effects) of anabnormal fluid attenuated inversion recovery signal in a brain MRIscan. Previous studies have demonstrated that the lumbar canalconstriction that causes the appearance of redundant nerve rootsalso leads, at the histologic level, to disarrangement and reduc-tion of the number of nerve fibers, demyelination, endoneuralfibrosis, and Schwann cell proliferation in these roots (13). On thebasis of such secondary histologic changes, it is not surprisingthat in a subset of patients presenting with such a radiologic sign,the long-term functional outcomes (in terms of both pain andfunction) remain poor even after adequate decompression of thespinal canal.Although the finding of redundant nerve roots in the cauda equinawasfirstdescribedmorethan50yearsagoinmyelographystudies(15),relativelylittleisknownaboutthepathophysiologyandclinicalsignificance of this radiologic phenomenon. A literature search atPubMed/Medlinewiththekeywords“redundantnerveroots”and“cauda equina” yielded only 29 indexed articles, with 25 of themhaving being published more than 20 years ago. Most of the olderreports focused not on the association between redundant nerverootsandlumbarcanalstenosisbutratheronthespecificradiologiccharacteristicsthatmighthelpdifferentiatesuchfindingsfromthepresence of arteriovenous spinal malformations in spinal myelo-grams(9,12).Asignthatanetiologicrelationshipbetweenlumbarcanal stenosis and the presence of redundant nerve roots (nowclearly appreciated) was not understood in those early days is thefactthatsomeofthesepreviousreportsevenproposedopeningoftheduramatertodisentanglethesupposedly“knottedandcurled”elongated nerve roots, followed by a questionable duraplasty torelieve the presumed “increased pressure” under which suchroots might be (9).Even today, the reality is that any statement regarding thepathophysiology of the appearance of redundant nerve roots inthe setting of lumbar canal stenosis remains purely speculative.One hypothesis is that the underlying etiology leading to such anabnormality would be essentially mechanical. Because previouspostmortem anatomic studies in patients with severe lumbarcanal stenosis have demonstrated that all redundant nerve rootspassed through the maximum point of constriction in the spinalcanal, it has been suggested that such squeezed roots would besignificantly stretched during concomitant leg and trunk exten-sion, ultimately leading to their elongation (13).Another possible etiology for such a finding would be a vascularabnormality in the cauda equina (related to either a compromisedarterial supply or an impaired venous drainage) induced by theconstrictive forces at the stenotic sites. Vascular changes have

Selective impairment of emotion recognition through music in Parkinson's disease: does it suggest the existence of different networks for music and speech prosody processing?

Although the main hallmark of Parkinsons disease (PD) are its motor symptoms, such as bradykinesia, resting tremor, postural instability, and rigidity, it has been increasingly recognized that such disease constitutes, in fact, a complex degenerative process which presents a variety of different clinical manifestations. Actually, in the last years, significant attention has been devoted to the so-called non-motor symptoms of PD, especially psychiatric ones, such as anxiety, depression, apathy, dysphoria and irritability, which have been shown to be present even in the early stages of disease (Leroi et al., 2012) and which show increasing intensity with its progression. Similarly, sleep disorders (such as difficulty for initiating sleep, frequent night awakenings, nocturia, restless legs syndrome, apnea, parasomnias and increased daytime sleepiness) have already been shown to occur with increased prevalence in patients with PD in comparison to the healthy population (Raggi et al., 2013). Nevertheless, the literature on the effects of PD upon other higher cognitive features, such as musical processing, is still scarce. Motivated by such increased attention to non-motor symptoms PD, and with basis on previous physiological studies which have demonstrated that the perception of music rhythm and beat is mediated mainly by the basal ganglia (the major anatomical complex involved in the etiology of PD) (Grahn, 2009), several recent studies have investigated the effects of PD over music perception. For example, it has already been shown that patients with PD have reduced capacity of synchronizing movements to a beat and, in turn, discriminating changes in tempo (“faster” vs. “slower”) (Grahn and Brett, 2009). Interestingly, such difficulty has been shown to be more marked when the beat is introduced at a slower tempo and progressively speeded up (McAuley et al., 2012). In such study, however, the capacity of patients with PD of discriminating changes in non “beat-based” rhythms did not significantly differ from that of a healthy control group. Ultimately, by correlating the impairment in beat perception with a decline in the coordinated functional activity between the basal ganglia, thalamus, premotor and supplementary motor regions, such studies have underscored the importance of the motor circuitry in beat perception. Nevertheless, in a recently published study, Lima et al. (2013) demonstrated that the effects of PD upon music perception may not be limited to rhythm detection, but may also involve the recognition of emotions as expressed through music. The authors of such investigation have demonstrated that patients with PD had increased difficulty to recognize happiness and peacefulness, when combinedly expressed through music lyrics and rhythm, while presenting intact perception of sadness and fear. Comparatively, in relation to non-musical speech, such patients presented only a mild global impairment of emotion recognition which seemed to be more a result of an executive dysfunction that a direct effect of the disease over the limbic system. Similarly, other previous investigations had already demonstrated that a dysfunction in the dopaminergic system may only partially explain the observed impairment in emotion recognition through facial expressions in patients with PD (Bediou et al., 2012), as the treatment with levodopa did not significantly modify such deficit. This finding was further confirmed by a recent meta-analysis on the issue (Gray and Tickle-Degnen, 2010). Conversely, in studies evaluating the effects of surgical treatment for Parkinson disease with deep brain stimulation (DBS), a therapeutic strategy which has been suggested to have broader effects in terms of modulating several interconnected circuits and not only the deep basal ganglia, it was possible to observe a synergistic improvement in the ability of recognizing the emotional content of facial expressions after combined treatment with both DBS and levodopa (Mondillon et al., 2012). In another study which also demonstrated impaired recognition of emotions as expressed through music in patients with PD, it was possible to observe that, although the observed deficit in fear recognition was at least partially associated with some degree of executive dysfunction, the deficit in emotion recognition in patients with PD persisted even after adjusting for executive functioning levels (van Tricht et al., 2010). Additionally, despite the fact that a previous study has suggested that depressed patients may have a negative emotional bias when evaluating musical stimuli (Punkanen et al., 2011), in this study the observed deficit in emotion recognition through music was not related to depressive symptoms, disease duration or severity of motor symptoms. All these results suggest that, although the observed impairment of emotion recognition through music in patients with PD may be partially related to a certain degree of executive dysfunction, it most likely reflect a separate primary cognitive deficit in emotional processing. The suggestion that it may be possible to localize specific cognitive features of emotional and music processing to single anatomical areas of the brain has been investigated by some recent studies which evaluated the neuroanatomical regions activated by facial and music recognition in patients with semantic dementia and Alzheimers disease (Omar et al., 2011). The results of such investigations demonstrated that the neurocognitive process involved in emotion recognition through facial expressions and music seems to be mediated by different but interconnected networks, with specific patterns of activation depending on the familiarity of the presented sensorial stimuli. In practical terms, the anterior tip of the right anterior temporal lobe seems to directly correlated with the ability to recognize famous tunes and famous faces, while the ability of identifying everyday tunes seems to activate the right mesial temporal structures, especially the amygdala (Hsieh et al., 2011). In opposition to the presented evidence which support the thesis that music and speech prosody may be mediated by different neurophysiological networks, several previous investigations have demonstrated a very close relationship between music perception and prosody (Thompson et al., 2004; Hutchins et al., 2010; Escoffier et al., 2013). Therefore, the verification of isolated effects of PD upon emotional processing through music perception (but not prosody) may consist in either a bias of the employed methodological approach, or an isolated effect related to motor-related rhythm dysfunction in patients with PD, rather than a true evidence of the existence of distinct networks for processing emotions (one musical and one non-musical) in normal physiological situations. Ultimately, further clinical and imaging studies are still required in order to confirm the validity of generalizing such findings in patients with PD to the healthy population. Finally, from a methodological standpoint, the findings of Lima et al. study suggest that future attempts of investigating the effects of degenerative diseases (as well as their treatment) upon the cognitive psychology of emotion processing should focus on specific neuropsychological domains (Hsieh et al., 2012), as there might be significant differences among the effects of such diseases upon recognition of emotional content from specific sensory inputs (for example, through visual or auditory modalities), and even among specific variations within one specific sensory modality (such as the difference between emotional recognition through musical and non-musical speech).

The secret is at the crossways: Hodotopic organization and nonlinear dynamics of brain neural networks

By integrating the classic psychological principles of ancient art of memory (AAOM) with the most recent paradigms in cognitive neuroscience (i.e., the concepts of hodotopic organization and nonlinear dynamics of brain neural networks), Llewellyn provides an up-to-date model of the complex psychological relationships between memory, imagination, and dreams in accordance with current state-of-the-art principles in neuroscience.

Primary and Metastatic Tumors of the Thoracolumbar Spine: Total En Bloc Spondylectomy

The management of spine tumors has progressively evolved over the past years. Advanced imaging modalities now allow early diagnosis of tumoral lesions and a better comprehension of the relationship between tumor, neural elements, and paraspinal structures. Also, progressive advances in surgical technology, radiation, and chemotherapy have led to the possibility of aggressive multimodal approach to the management of selected spine tumors, resulting in improved patient care.

Neuroimaging for Surgical Treatment Planning of Neoplastic Disease of the Spine

Abstract In patients with new-onset low-back pain the cause is usually benign in origin. Nonetheless spinal cancer might present for the first time as an episode of new-onset back or neck pain. Therefore imaging studies are essential in evaluating back pain in patients with a previous history of cancer. Such imaging exams are valuable tools for generating the most likely diagnosis based on imaging characteristics as well as for orienting further imaging-guided biopsy. Computed tomography scan and magnetic resonance imaging (MRI) are essential in the surgical planning to address the extent of disease, the affected spinal compartments, and the degree of bone involvement. Contrasted MRIs are crucial to evaluate bone infiltration, intradural tumors, and spinal cord compression. MRI tractography might be used to guide the resection of intramedullary lesions. Angiography can be used to evaluate vascularity of certain types of tumor and it might be followed by preoperative embolization as an attempt to decrease intraoperative bleeding. Additionally, angiography is essential to evaluate the vertebral arteries in cases of en bloc resection of cervical primary bone tumors. Ultimately the combination of multimodal imaging studies affects decision-making in vertebroplasty, screw placement, and type of approach and aggressiveness of surgical intervention procedure.

The validity of Dawkins's selfish gene theory and the role of the unconscious in decision making.

Although the proposed Selfish Goal Theory constitutes a major theoretical tour de force for addressing the issue of inconsistencies in human actions and the role of motivational goals in behavior, as it is based on an unproven biological paradigm (Dawkinss selfish gene theory) and overemphasizes the role of unconscious processes in decision making, it provides a questionable model of the underlying psychological structure of human agency.