Jessica Peter

Dr. Jessica Peter

University Hospital of Old Age Psychiatry and Psychotherapy, University of Bern
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Research Focus & Metrics

Academic Career Length

14Years (2013-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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30 August 2017 in Human Brain Mapping
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Journal Article
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LMLora Minkova
Lora Minkova
AHAnnegret Habich
Annegret Habich
JPJessica Peter
Jessica Peter
CKChristoph P. Kaller
Christoph P. Kaller
SESimon B. Eickhoff
Simon B. Eickhoff
SKStefan Klöppel
Stefan Klöppel

17 July 2013 in Alzheimer's & Dementia
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Journal Article
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JPJessica Peter
Jessica Peter
LSLukas Scheef
Lukas Scheef
AAAhmed Abdulkadir
Ahmed Abdulkadir
HBHenning Boecker
Henning Boecker
MHMichael Heneka
Michael Heneka
AIAlzheimer'S Disease Neuroimaging Initiative
Alzheimer'S Disease Neuroimaging Initiative

2 December 2020 in Brain Sciences
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KKKatharina Klink
Katharina Klink
SPSven Paßmann
Sven Paßmann
FKFlorian Kasten
Florian Kasten
JPJessica Peter
Jessica Peter
Transcranial alternating current stimulation (tACS) is a non-invasive brain stimulation technique that allows the manipulation of intrinsic brain oscillations. Numerous studies have applied tACS in the laboratory to enhance cognitive performance. With this systematic review, we aim to provide an overview of frequency-specific tACS effects on a range of cognitive functions in healthy adults. This may help to transfer stimulation protocols to real-world applications. We conducted a systematic literature search on PubMed and Cochrane databases and considered tACS studies in healthy adults (age > 18 years) that focused on cognitive performance. The search yielded n = 109 studies, of which n = 57 met the inclusion criteria. The results indicate that theta-tACS was beneficial for several cognitive functions, including working memory, executive functions, and declarative memory. Gamma-tACS enhanced performance in both auditory and visual perception but it did not change performance in tasks of executive functions. For attention, the results were less consistent but point to an improvement in performance with alpha- or gamma-tACS. We discuss these findings and point to important considerations that would precede a transfer to real-world applications.

11 August 2015 in Journal of Alzheimer’s Disease
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SKStefan Klöppel
Stefan Klöppel
JPJessica Peter
Jessica Peter
ALAnna Ludl
Anna Ludl
APAnne Pilatus
Anne Pilatus
SMSabrina Maier
Sabrina Maier
F1For The Alzheimer’S Disease Neuroimaging Initiative 1
For The Alzheimer’S Disease Neuroimaging Initiative 1
Several studies have demonstrated that fully automated pattern recognition methods applied to structural magnetic resonance imaging (MRI) aid in the diagnosis of dementia, but these conclusions are based on highly preselected samples that significantly differ from that seen in a dementia clinic. At a single dementia clinic, we evaluated the ability of a linear support vector machine trained with completely unrelated data to differentiate between Alzheimer’s disease (AD), frontotemporal dementia (FTD), Lewy body dementia, and healthy aging based on 3D-T1 weighted MRI data sets. Furthermore, we predicted progression to AD in subjects with mild cognitive impairment (MCI) at baseline and automatically quantified white matter hyperintensities from FLAIR-images. Separating additionally recruited healthy elderly from those with dementia was accurate with an area under the curve (AUC) of 0.97 (according to Fig. 4 ). Multi-class separation of patients with either AD or FTD from other included groups was good on the training set (AUC > 0.9) but substantially less accurate (AUC = 0.76 for AD, AUC = 0.78 for FTD) on 134 cases from the local clinic. Longitudinal data from 28 cases with MCI at baseline and appropriate follow-up data were available. The computer tool discriminated progressive from stable MCI with AUC = 0.73, compared to AUC = 0.80 for the training set. A relatively low accuracy by clinicians (AUC = 0.81) illustrates the difficulties of predicting conversion in this heterogeneous cohort. This first application of a MRI-based pattern recognition method to a routine sample demonstrates feasibility, but also illustrates that automated multi-class differential diagnoses have to be the focus of future methodological developments and application studies

9 December 2013 in PLOS ONE
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MKMiriam Kunz
Miriam Kunz
JPJessica Peter
Jessica Peter
SHSonja Huster
Sonja Huster
Stefan LautenbacherStefan Lautenbacher
Stefan Lautenbacher
The experience of pain and disgust share many similarities, given that both are aversive experiences resulting from bodily threat and leading to defensive reactions. The aim of the present study was to investigate whether facial expressions are distinct enough to encode the specific quality of pain and disgust or whether they just encode the similar negative valence and arousal level of both states. In sixty participants pain and disgust were induced by heat stimuli and pictures, respectively. Facial responses (Facial Action Coding System) as well as subjective responses were assessed. Our main findings were that nearly the same single facial actions were elicited during pain and disgust experiences. However, these single facial actions were displayed with different strength and were differently combined depending on whether pain or disgust was experienced. Whereas pain was mostly encoded by contraction of the muscles surrounding the eyes (by itself or in combination with contraction of the eyebrows); disgust was mainly accompanied by contraction of the eyebrows and—in contrast to pain—by raising of the upper lip as well as the combination of upper lip raise and eyebrow contraction. Our data clearly suggests that facial expressions seem to be distinct enough to encode not only the general valence and arousal associated with these two bodily aversive experiences, namely pain and disgust, but also the specific origin of the threat to the body. This implies that the differential decoding of these two states by an observer is possible without additional verbal or contextual information, which is of special interest for clinical practice, given that raising awareness in observers about these distinct differences could help to improve the detection of pain in patients who are not able to provide a self-report of pain (e.g., patients with dementia).

17 March 2020 in Frontiers in Aging Neuroscience
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KKKatharina Klink
Katharina Klink
JPJessica Peter
Jessica Peter
PWPatric Wyss
Patric Wyss
SKStefan Klöppel
Stefan Klöppel
Associative memory is one of the first cognitive functions negatively affected by healthy and pathological aging processes. Non-invasive brain stimulation (NIBS) techniques are easily administrable tools to support memory. However, the optimal stimulation parameters inducing a reliable positive effect on older adult’s memory performance remain mostly unclear. In our randomized, double-blind, cross-over study, 28 healthy older adults (16 females; 71.18 + 6.42 years of age) received anodal transcranial direct (tDCS), alternating current in the theta range (tACS), and sham stimulation over the left ventrolateral prefrontal cortex (VLPFC) each once during encoding. We tested associative memory performance with cued recall and recognition tasks after a retention period and again on the following day. Overall, neither tDCS nor tACS showed effects on associative memory performance. Further analysis revealed a significant difference for performance on the cued recall task under tACS compared to sham when accounting for age. Our results suggest that tACS might be more effective to improve associative memory performance than tDCS in higher aged samples.