Neurophysiological Investigation of the Functional Interactions between Manual Action Control and Working Memory

Gündüz Can R. Neurophysiological Investigation of the Functional Interactions between Manual Action Control and Working Memory. Bielefeld: Universität Bielefeld; 2020

Movement Interferes with Visuospatial Working Memory during the Encoding: An ERP Study

Gündüz Can R, Schack T, Koester D. Movement Interferes with Visuospatial Working Memory during the Encoding: An ERP Study. Frontiers in Psychology. 2017;8(871): 1-16.The present study focuses on the functional interactions of cognition and manual action control. Particularly, we investigated the neurophysiological correlates of the dual-task costs of a manual-motor task (requiring grasping an object, holding it, and subsequently placing it on a target) for working memory (WM) domains (verbal and visuospatial) and processes (encoding and retrieval). Thirty participants were tested in a cognitive-motor dual-task paradigm, in which a single block (a verbal or visuospatial WM task) was compared with a dual block (concurrent performance of a WM task and a motor task). Event-related potentials (ERPs) were analyzed separately for the encoding and retrieval processes of verbal and visuospatial WM domains both in single and dual blocks. The behavioral analyses show that the motor task interfered with WM and decreased the memory performance. The performance decrease was larger for the visuospatial task compared with the verbal task, i.e., domain-specific memory costs were obtained. The ERP analyses show the domain-specific interference also at the neurophysiological level, which is further process-specific to encoding. That is, comparing the patterns of WM-related ERPs in the single block and dual block, we showed that visuospatial ERPs changed only for the encoding process when a motor task was performed at the same time. Generally, the present study provides evidence for domain- and process-specific interactions of a prepared manual-motor movement with WM (visuospatial domain during the encoding process). This study, therefore, provides an initial neurophysiological characterization of functional interactions of WM and manual actions in a cognitive-motor dual-task setting, and contributes to a better understanding of the neuro-cognitive mechanisms of motor action control

The neurophysiology of the interference of grasping movements in functionally separate working memory processes

Gündüz Can R, Schack T, Koester D. The neurophysiology of the interference of grasping movements in functionally separate working memory processes. In: Funke J, Rummel J, Voß A, eds. Abstracts of the 58th Conference of Experimental Psychologists (TeaP 2016). Lengerich: Pabst Science Publishers; 2016: 111

Movement (re-)planning interferes with working memory during the maintenance process: An ERP study

Gündüz Can R, Schack T, Koester D. Movement (re-)planning interferes with working memory during the maintenance process: An ERP study. In: Schütz A, Schubö A, Endres D, Lachnit H, eds. 60. TeaP 2018. Abstracts of the 60. conference of experimental psychologists: March, 11th to 14th Marburg, Germany. Lengerich: Pabst; 2018: 98

The neurophysiological interaction between working memory and grasping movements

Gündüz Can R, Schack T, Koester D. The neurophysiological interaction between working memory and grasping movements. In: Barkowsky T, Llanosa ZF, Schultheis H, van de Ven J, eds. Spatial cognition 13th biannual conference of the German cognitive science scociety. 2016: S.123-125

Kanserli dokuların mikroskop görüntülerinde kanser kök hücre oranın otomatik olarak belirlenmesi ve klinikte kullanılacak yazılım geliştirilmesi

TÜBİTAK EEEAG01.12.2016Kanser anormal hücrelerin kontrolsüz çoğalması ve yayılması olarak tanımlanan karmaşık bir hastalıktır. Bu nedenle kanser dokusu farklı özellikleri olan-ek popülasyon denilen-hücre gruplarını içerir. Bu hücrelerden olan kanser kök hücreleri normal kök hücreleri gibi kendini yenileme ve farklılaşma özelliklerini taşırken normal kök hücrelerinin aksine homeostatik kontrolleri olmayan, yani farklılaşma özelliklerini dengeleyip, çevresel sinyallere göre programlama özellikleri olmayan hücrelerdir. Bu özellikleri dolayısıyla da son yıllarda kanser kök hücre popülasyonu kanserin kötü prognozundan sorumlu hücreler olarak tanımlanmaktadırlar. Bu bağlamda kanser tedavisinde kanser kök hücre oran bilgisi, hastaya verilecek tedavinin planlanması amacıyla kullanılabilir. Hekimler kanserli dokunun kanser kök hücre popülasyon onarına göre henüz kanser metastaz yapmamış bile olsa bireye özgü tedavi yaklaşımı izlenebilir. Gerçekleştirilen bu proje kapsamında, kanserli parafin bloklara gömülü doku biyopsi örneklerinde, kanser kök hücre tanımlama öngörü aracını geliştirdik. Kovaryans matrisine dayalı sınıflandırıcılara ve Ana Bileşenler Analizi (PCA) algoritması sonucunda üç sınıf H&E boyanmış karaciğer kanseri dokularının sınıflandırma probleminde 76.0% imge sınıflandırma başarısı elde edilmiştir. Ana Bileşenler Analizi kanser hücresi belirleme probleminde %90’nın üstünde başarı ve kovaryans matrisine dayalı sınıflandırıcılar ile üç sınıf ayrıştırma probleminde %90’a yakın başarı sağlanmıştır. Kanserli hastalarda bireye ve hedefe yönelik tedavi yol haritasının belirlenmesine destek olabilecek ve hastalığın tedavisinde ve prognozunda iyileştirme sağlayabilecek yazılımı hekimlerin kullanıma sunduk. CANSTEM yazılıma http://users.metu.edu.tr/rengul/canstem.html adresinden ulaşılabilir.Cancer is a complex disease characterized by uncontrolled cell proliferation and metastasis. For this reason, cancer tissue includes cell groups called side-population, which have different properties. Similar to the normal stem cells, cancer stem cells possess self- renewing and differentiation capacities but lack homeostatic controls. Cancer stem cells don’t respond to the external which control growth regulation and differentiation. Because of these features, cancer stem cells in recent years have been described as cell populations responsible for the poor prognosis of cancer. In this context, cancer stem cell ratio information can be used to plan the treatment. Physicians can monitor the individualized treatment approach even if the cancer has not yet metastasized at early stage. Within the scope of this project, we developed a cancer stem cell prediction tool in cancerous tissue biopsy specimens embedded in paraffin blocks. Classification based on the covariance matrix and PCA algorithm resulted in 76.0% image classification success for the classification H&E stained liver cancer tissues. The Principal Component Analysis achieved over 90% success and the covariance matrix in the classification problem of three classes had a success nearly 90% in cancer detection. The newly developed CANSTEM software allows the identification cancer stem cell ratio in cancer tissues for individualized and targeted treatment and prognosis of the disease. CANSTEM software is available at http://users.metu.edu.tr/rengul/canstem.html