Brain enhancement through cognitive training: A new insight from brain connectome

Owing to the recent advances in neurotechnology and the progress in understanding of brain cognitive functions, improvements of cognitive performance or acceleration of learning process with brain enhancement systems is not out of our reach anymore, on the contrary, it is a tangible target of contemporary research. Although a variety of approaches have been proposed, we will mainly focus on cognitive training interventions, in which learners repeatedly perform cognitive tasks to improve their cognitive abilities. In this review article, we propose that the learning process during the cognitive training can be facilitated by an assistive system monitoring cognitive workloads using electroencephalography (EEG) biomarkers, and the brain connectome approach can provide additional valuable biomarkers for facilitating leaners' learning processes. For the purpose, we will introduce studies on the cognitive training interventions, EEG biomarkers for cognitive workload, and human brain connectome. As cognitive overload and mental fatigue would reduce or even eliminate gains of cognitive training interventions, a real-time monitoring of cognitive workload can facilitate the learning process by flexibly adjusting difficulty levels of the training task. Moreover, cognitive training interventions should have effects on brain sub-networks, not on a single brain region, and graph theoretical network metrics quantifying topological architecture of the brain network can differentiate with respect to individual cognitive states as well as to different individuals' cognitive abilities, suggesting that the connectome is a valuable approach for tracking the learning progress. Although only a few studies have exploited the connectome approach for studying alterations of the brain network induced by cognitive training interventions so far, we believe that it would be a useful technique for capturing improvements of cognitive function

Neuroplasticity Subserving Motor Skill Learning

Recent years have seen significant progress in our understanding of the neural substrates of motor skill learning. Advances in neuroimaging provide new insight into functional reorganization associated with the acquisition, consolidation, and retention of motor skills. Plastic changes involving structural reorganization in gray and white matter architecture that occur over shorter time periods than previously thought have been documented as well. Data from experimental animals provided crucial information on plausible cellular and molecular substrates contributing to brain reorganization underlying skill acquisition in humans. Here, we review findings demonstrating functional and structural plasticity across different spatial and temporal scales that mediate motor skill learning while identifying converging areas of interest and possible avenues for future research

Evaluating The Relationship Between Short- and Long-Term Neural Adaptations to Motor Skill Acquisition and Retention

Attempting to understand the neurophysiological underpinnings of learned behaviors and the process of learning itself has yielded interesting findings relating to what happens in the brain and across the nervous system when learning a new skill. The nervous system displays several structural, functional and neurochemical adaptations to motor learning which have been highlighted through the use of neuroimaging techniques such as fMRI, EEG and TMS. This review attempts to outline the neural adaptations governing the acquisition and retention of motor skills, as well as build a timeline for these adaptations following Fitt’s model of motor learning (Fitts and Posner 1967). As one moves across the stages of learning (cognitive, associative, autonomous) the nervous system displays an initial increase in activity and plasticity in the frontal associative regions, motor cortical regions, parietal cortices, sensorimotor striatum, associative striatum, cerebral cortices and nuclei and hippocampus (Doyon et al., 2008), as well as the basal ganglia thalamocortical loops, medial cerebellum, anterior cingulate cortex, inferior frontal gyrus and the visual and parietal cortical areas (Seidler 2011). These neuro-plastic adaptations and activation patterns cement and refine themselves in later stages, indicating a more efficient circuitry and decreased cognitive load when performing the skill (Poldrack et al., 2005). In terms of practical applications of these findings, manipulation of the training principles involved in specific contexts of motor skill learning such as training specificity, duration and intensity, may yield improved neural adaptations and in turn performance on the skill in question

Investigating the Cortical, Metabolic and Behavioral Effects of Transcranial Direct Current Stimulation in Preparation for Combined Rehabilitation

The goal of this thesis was to determine the cortical reorganization that occurs in patients with cervical spondylotic myelopathy (CSM) after surgical decompression and to implement this knowledge into a new rehabilitation strategy. Transcranial direct current stimulation (tDCS) is a non-invasive technique to modulate human behavior. Due to the novel electrode montage used, it was first pertinent that we determine how tDCS would modulate cortical, metabolic and motor behavior in healthy individuals. We observed the longitudinal functional adaptations that occur in patients with CSM using functional MRI. Enhanced excitation of supplementary motor area (SMA) was observed following surgical decompression and associated with increased function following surgery. This novel finding of enhanced excitation of motivated us to use a bihemispheric tDCS protocol, exciting bilateral motor areas to provide optimal motor enhancement. This novel tDCS electrode montage, targeting the SMA and primary motor cortex (M1) was implemented in healthy older adults to determine its effects on enhancing manual dexterity. Furthermore, to determine the frequency with which to apply tDCS, a single and tri session protocol was used. We observed a differential pattern of action with anti-phase and in-phase motor tasks during multisession tDCS. We used ultra-high field (7T) MRI to examined the metabolic changes that occur following tDCS. After the stimulation period we observed no significant metabolite modulation. A trend towards an increase in the NAA/tCr ratio, with a concomitant decrease in the absolute concentration of tCr was observed. Finally, we examined the functional connectivity before, during and after tDCS with the use of resting-state fMRI at 7T. We observed enhanced connectivity within right sensorimotor area after stimulation compared to during stimulation. This result confirmed that cortical modulations differ during versus after tDCS, signifying that optimal modulation of behaviour may be after the stimulation period. Furthermore, we observed an enhanced correlation between motor regions and the caudate, both during and after stimulation. In conclusion, we observed novel cortical adaptations in CSM patients after surgical decompression, which led us to believe that bihemispheric tDCS of M1-SMA network would result in optimal motor enhancement and warrants further investigation in CSM and other neurological disorders

The malleable brain: plasticity of neural circuits and behavior: A review from students to students

One of the most intriguing features of the brain is its ability to be malleable, allowing it to adapt continually to changes in the environment. Specific neuronal activity patterns drive long-lasting increases or decreases in the strength of synaptic connections, referred to as long-term potentiation (LTP) and long-term depression (LTD) respectively. Such phenomena have been described in a variety of model organisms, which are used to study molecular, structural, and functional aspects of synaptic plasticity. This review originated from the first International Society for Neurochemistry (ISN) and Journal of Neurochemistry (JNC) Flagship School held in Alpbach, Austria (Sep 2016), and will use its curriculum and discussions as a framework to review some of the current knowledge in the field of synaptic plasticity. First, we describe the role of plasticity during development and the persistent changes of neural circuitry occurring when sensory input is altered during critical developmental stages. We then outline the signaling cascades resulting in the synthesis of new plasticity-related proteins, which ultimately enable sustained changes in synaptic strength. Going beyond the traditional understanding of synaptic plasticity conceptualized by LTP and LTD, we discuss system-wide modifications and recently unveiled homeostatic mechanisms, such as synaptic scaling. Finally, we describe the neural circuits and synaptic plasticity mechanisms driving associative memory and motor learning. Evidence summarized in this review provides a current view of synaptic plasticity in its various forms, offers new insights into the underlying mechanisms and behavioral relevance, and provides directions for future research in the field of synaptic plasticity.Fil: Schaefer, Natascha. University of Wuerzburg; AlemaniaFil: Rotermund, Carola. University of Tuebingen; AlemaniaFil: Blumrich, Eva Maria. Universitat Bremen; AlemaniaFil: Lourenco, Mychael V.. Universidade Federal do Rio de Janeiro; BrasilFil: Joshi, Pooja. Robert Debre Hospital; FranciaFil: Hegemann, Regina U.. University of Otago; Nueva ZelandaFil: Jamwal, Sumit. ISF College of Pharmacy; IndiaFil: Ali, Nilufar. Augusta University; Estados UnidosFil: García Romero, Ezra Michelet. Universidad Veracruzana; MéxicoFil: Sharma, Sorabh. Birla Institute of Technology and Science; IndiaFil: Ghosh, Shampa. Indian Council of Medical Research; IndiaFil: Sinha, Jitendra K.. Indian Council of Medical Research; IndiaFil: Loke, Hannah. Hudson Institute of Medical Research; AustraliaFil: Jain, Vishal. Defence Institute of Physiology and Allied Sciences; IndiaFil: Lepeta, Katarzyna. Polish Academy of Sciences; ArgentinaFil: Salamian, Ahmad. Polish Academy of Sciences; ArgentinaFil: Sharma, Mahima. Polish Academy of Sciences; ArgentinaFil: Golpich, Mojtaba. University Kebangsaan Malaysia Medical Centre; MalasiaFil: Nawrotek, Katarzyna. University Of Lodz; ArgentinaFil: Paid, Ramesh K.. Indian Institute of Chemical Biology; IndiaFil: Shahidzadeh, Sheila M.. Syracuse University; Estados UnidosFil: Piermartiri, Tetsade. Universidade Federal de Santa Catarina; BrasilFil: Amini, Elham. University Kebangsaan Malaysia Medical Centre; MalasiaFil: Pastor, Verónica. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Biología Celular y Neurociencia ; ArgentinaFil: Wilson, Yvette. University of Melbourne; AustraliaFil: Adeniyi, Philip A.. Afe Babalola University; NigeriaFil: Datusalia, Ashok K.. National Brain Research Centre; IndiaFil: Vafadari, Benham. Polish Academy of Sciences; ArgentinaFil: Saini, Vedangana. University of Nebraska; Estados UnidosFil: Suárez Pozos, Edna. Instituto Politécnico Nacional; MéxicoFil: Kushwah, Neetu. Defence Institute of Physiology and Allied Sciences; IndiaFil: Fontanet, Paula. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Biología Celular y Neurociencia ; ArgentinaFil: Turner, Anthony J.. University of Leeds; Reino Unid

Functional connectivity in relation to motor performance and recovery after stroke.

Plasticity after stroke has traditionally been studied by observing changes only in the spatial distribution and laterality of focal brain activation during affected limb movement. However, neural reorganization is multifaceted and our understanding may be enhanced by examining dynamics of activity within large-scale networks involved in sensorimotor control of the limbs. Here, we review functional connectivity as a promising means of assessing the consequences of a stroke lesion on the transfer of activity within large-scale neural networks. We first provide a brief overview of techniques used to assess functional connectivity in subjects with stroke. Next, we review task-related and resting-state functional connectivity studies that demonstrate a lesion-induced disruption of neural networks, the relationship of the extent of this disruption with motor performance, and the potential for network reorganization in the presence of a stroke lesion. We conclude with suggestions for future research and theories that may enhance the interpretation of changing functional connectivity. Overall findings suggest that a network level assessment provides a useful framework to examine brain reorganization and to potentially better predict behavioral outcomes following stroke

Functional Connectivity in the Motor Network Largely Matures Before Motor Function

The brain changes in many ways in the first year. It is not known which of these changes are most critical for the development of cognitive functions. According to the Interactive Specialization Theory, developments in behaviour result from changes in brain connectivity. We tested this using functional connectivity magnetic resonance imaging (fcMRI) of the motor system. fcMRI was acquired at three and nine months – two time-points between which motor behaviour develops enormously. Infants were additionally compared with adults. Subjects were scanned with a 3T MRI scanner, yielding BOLD signal time-courses that were correlated with one another. Our results do not support the Interactive Specialization Theory, as connectivity did not change with motor development and instead was adult-like in the youngest infants. fcMRI has enabled deeper exploration of network connectivity patterns and continues to emerge as a leading method in infant neuroscience

Neuroplasticity of language networks in aphasia: advances, updates, and future challenges

Researchers have sought to understand how language is processed in the brain, how brain damage affects language abilities, and what can be expected during the recovery period since the early 19th century. In this review, we first discuss mechanisms of damage and plasticity in the post-stroke brain, both in the acute and the chronic phase of recovery. We then review factors that are associated with recovery. First, we review organism intrinsic variables such as age, lesion volume and location and structural integrity that influence language recovery. Next, we review organism extrinsic factors such as treatment that influence language recovery. Here, we discuss recent advances in our understanding of language recovery and highlight recent work that emphasizes a network perspective of language recovery. Finally, we propose our interpretation of the principles of neuroplasticity, originally proposed by Kleim and Jones (1) in the context of extant literature in aphasia recovery and rehabilitation. Ultimately, we encourage researchers to propose sophisticated intervention studies that bring us closer to the goal of providing precision treatment for patients with aphasia and a better understanding of the neural mechanisms that underlie successful neuroplasticity.P50 DC012283 - NIDCD NIH HHSPublished versio