Merav Ahissar Lab

ELSC Members

Joseph H. and Belle R. Braun Chair in Psychology
Human Perceptual and cognitive learning

Skill acquisition

Perception, memory, and reasoning have traditionally been studied separately. I am interested in the relations between these mental operations and in the dynamics of these relations as people practice and become experts. I am further interested in deciphering which mechanisms malfunction in the cases where practice does not lead to expertise, like the case of reading disability (dyslexia) in spite of huge amount of practice.

Conceptual frameworks for learning

1.Top-down: task driven learning

The Reverse Hierarchy Theory of perception and learning, which explains learning processes as a top-down driven processes, which proceeds backwards – and task-induced learning processes that begin at the “top” of the hierarchies and proceed by a backward search for the most informative inputs (neural populations).

2.Bottom-up: Statistical Bayesian learning

The poor-anchoring (and faster memory decay) theory of dyslexia, which explains the difficulties of dyslexics in acquiring reading expertise as a consequence of faster decay of perceptual traces, which leads to a shallower long-term learning slope, manifesting slower accumulation of linguistics (and non-linguistic) regularities.

The slow-update theory of autism, which proposes that high-functioning individuals with autism (no language difficulties) are slow in updating their perceptual predictions and their motor plans – which impedes online interactions, both social and non-social.

Techniques

We use behavioral task, and use computational models to decipher and quantify underlying mechanisms.
We use ERP to assess within-trial dynamics of task preparation, neuronal adaptation and their relation to behavior.
We use fMRI to assess cross-trial dynamics and “division of labor” between various cortical and sub-cortical regions.

Merav Ahissar

Professor

Phone: +972-2-5883409
Address: The Edmond and Lily Safra Center for Brain Sciences
The Suzanne and Charles Goodman Brain Sciences Building,
Level 1, Room 1103, Edmond J. Safra Campus,
The Hebrew University of Jerusalem, 9190401
Joseph H. and Belle R. Braun Chair in Psychology
Human Perceptual and cognitive learning

Skill acquisition

Perception, memory, and reasoning have traditionally been studied separately. I am interested in the relations between these mental operations and in the dynamics of these relations as people practice and become experts. I am further interested in deciphering which mechanisms malfunction in the cases where practice does not lead to expertise, like the case of reading disability (dyslexia) in spite of huge amount of practice.

Conceptual frameworks for learning

1.Top-down: task driven learning

The Reverse Hierarchy Theory of perception and learning, which explains learning processes as a top-down driven processes, which proceeds backwards – and task-induced learning processes that begin at the “top” of the hierarchies and proceed by a backward search for the most informative inputs (neural populations).

2.Bottom-up: Statistical Bayesian learning

The poor-anchoring (and faster memory decay) theory of dyslexia, which explains the difficulties of dyslexics in acquiring reading expertise as a consequence of faster decay of perceptual traces, which leads to a shallower long-term learning slope, manifesting slower accumulation of linguistics (and non-linguistic) regularities.

The slow-update theory of autism, which proposes that high-functioning individuals with autism (no language difficulties) are slow in updating their perceptual predictions and their motor plans – which impedes online interactions, both social and non-social.

Techniques

We use behavioral task, and use computational models to decipher and quantify underlying mechanisms.
We use ERP to assess within-trial dynamics of task preparation, neuronal adaptation and their relation to behavior.
We use fMRI to assess cross-trial dynamics and “division of labor” between various cortical and sub-cortical regions.

Ayelet
Ayelet Gertsovski
PhD Student
Keren_photo
Keren Kasten
PhD Student
Michal_Dobner_Ives
Michal Dobner Ives
PhD Student
Noam-Khayat
Noam Khayat
PhD Student
Passport_tamar1 (1)
Tamar Malinovitch
PhD Student
עמוס_בועזסון_תמונה_2020_narrow_3
Amos Boasson
Post Doc
photo_for_lab_cropped
Eli Fivelzon
Undergraduate Student, Programmer
ELSC-Nathaniel-Zuk
Nathaniel Zuk
Post Doc
ELSC-Seminars-General
Mor Nahum
ELSC-Seminars-General
Keren Banai
ELSC-Seminars-General
Gal Ben Yehudah
ELSC-Seminars-General
Sygal Amitay
ELSC-Seminars-General
Yehoshua Rosenberg
ELSC-Seminars-General
Ariel Rokem
ELSC-Seminars-General
Yulia Oganian
ELSC-Seminars-General
Mark Shovman
ELSC-Seminars-General
Ofri Raviv
ELSC-Seminars-General
Nori Jacoby
ELSC-Seminars-General
Sagi Jaffe Dax
Luba_Daikhin
Luba Daikhin
ELSC-Seminars-General
Olga Aizenberg
Itamar
Itamar Kinreich
Odeya_guri
Odeya Guri
Shahaf_Granot
Shahaf Granot
ELSC-Seminars-General
Atalia Hai
Eva_Kimel
Eva Kimel
Itay_Lieder
Itay Lieder
Gal Vishne, Nori Jacoby, Tamar Malinovitch, Tamir Epstein, Or Frenkel & Merav Ahissar

Nature Communications,12, 5439 (2021)

Malinovitch, T., Jakoby, H. & Ahissar, M.

Psychon Bull Rev (2020)

Kimel, E., Hai Weiss A., Jakoby H., Daikhin L., & Ahissar M

Neuropsychologia (2020)

Kimel, E., & Ahissar, M

Journal of Experimental Psychology: Learning, Memory, and Cognition 46(1), 155-169 (2020)

Tamar Malinovitch, Hilla Jackoby, Merav Ahissar

bioRxiv (2020)

Kimel E and Ahissar M

Front. Young Minds. 8:61 (2020)

Jakoby H , Raviv O, Jaffe-Dax S, Lieder I, Ahissar M

Journal of Experimental Psychology: General (2019)

Itay Lieder, Vincent Adam, Or Frenkel, Sagi Jaffe-Dax, Maneesh Sahani & Merav Ahissar

Nature Neurosciencevolume 22, pages256–264 (2019)

Daikhin, L, Raviv O, Ahissar M.

Journal of Speech, Language, and Hearing Research, Volume 60, Issue 2, Page: 471-479 (2017)

Banai, K, Ahissar M.

Language, Cognition and Neuroscience, Volume 33, Issue 3, Pages 321-332 (2017)

Jaffe-Dax, S, Lieder I, Biron T, Ahissar M.

Journal of Vision, Vol.16, 10 (2016)

Jaffe-Dax S, Raviv O, Jacoby N, Loewenstein Y, Ahissar M.

J Neurosci. 2015 Sep 2;35(35):12116-26. (2015)

Nori Jacoby, Peter E. Keller, Bruno H. Repp, Naftali Tishby, Merav Ahissar

Timing & Time Perception, Volume 3: Issue 1-2 (2015)

Nori Jacoby, Naftali Tishby, Bruno H. Repp, Merav Ahissar and Peter E. Keller

Timing & Time Perception, Volume 3: Issue 1-2 (2015)

Ofri Raviv, Itay Lieder, Yonatan Loewenstein, and Merav Ahissar

PLoS Comput Biol. 2014 Dec; 10(12): e1003948. (2014)

Ofri Raviv , Merav Ahissar, Yonatan Loewenstein

PLoS Computational Biology 8(10):e1002731 (2012)

Nahum M, Nelken I, Ahissar M.

Vision Res. 2010 Feb 22;50(4):391-401. (2010)

Merav Ahissar , Mor Nahum , Israel Nelken and Shaul Hochstein

Philosophical transactions of the Royal Society of London. Series B, Biological sciences (2009)

Nahum M, Nelken I, Ahissar M.

PLoS Biol. 2008 May 20;6(5):e126. (2008)

Amitay S, Ahissar M, Nelken I.

J Assoc Res Otolaryngol. 2002 Sep;3(3):302-20. (2002)

Ehud Ahissar, Moshe Abeles, Merav Ahissar, Sebastian Haidarliu, Eilon Vaadia

Neuropharmacology 37(4-5):633-55 (1998)

Ahissar E, Vaadia E, Ahissar M, Bergman H, Arieli A, Abeles M.

Science. 1992 Sep 4;257(5075):1412-5. (1992)

Interested people are welcome to contact the lab.
Memory, learning & perception: Funding & Research Projects: 1. ERC – ADVANCED – NEUROCOMPSKILL
Understanding the failure of acquiring reading and social expertise (dyslexia and autism) within a unified framework of skill acquisition

Why do most people acquire expertise with practice whereas others fail to master the same tasks? NeuroCompSkill offers a neuro-computational framework that explains failure in acquiring verbal and non-verbal communication skills. It focuses on individual ability in using task-relevant regularities, postulating that efficient use of such regularities is crucial for acquiring expertise. Specifically, it proposes that using stable temporal regularities, acquired across long time windows (> 3 sec to days) is crucial for the formation of linguistic (phonological, morphological and orthographic) skills. In contrast, fast updating of recent events (within ~ .3- 3 sec), is crucial for the formation of predictions in interactive, social communication. Based on this, we propose that individuals with difficulties in retaining regularities will have difficulties in verbal communication, whereas individuals with difficulties in fast updating will have difficulties in social non-verbal communications

Sensitivity to sound statistics: an indication in skill acquisition -Prof. Merav Ahissar -2019

2. ISF
Perceptual learning: the role of learning stimulus statistics

Practice based improvement is a main characteristic of human behavior. This applies even to basic perceptual processes. But what is it that improves? Is it the accuracy of our sensory representations, or the validity of our implicit predictions? Since perception is an integrative process, which implicitly merges information from incoming stimuli with experience-based knowledge of the world, improvement can stem from either, or both. Recent conceptual developments, such as introduction of Bayesian framework to cognitive neuroscience, offer new tools and insights for addressing this question. The Bayesian framework views perception as the posterior outcome of integrating (multiplying) the sensory response (likelihood) with knowledge about statistics of stimuli in the world (prior), allowing quantitative estimates of the contribution of each component to the resulting perceptual performance. However, the Bayesian framework does not specify how the prior is learned. We now aim to study the dynamics of learning the prior, which is not initially available to the performer, and may itself change. Here we use the term – “prediction”, referring to participants’ “belief” regarding the statistics of stimuli in the world. We shall characterize these predictions as a function of the trained conditions, at the behavioral and neural levels, in three different populations: general adult population, adult dyslexics and children, whose pattern of forming predictions is expected to differ. Autism:

Perceptual bias reveals slow updating in autism and fast forgetting in dyslexia-Prof. Merav Ahissar-2019

Dyslexia:
New Findings on Dyslexia May Aid Diagnosis, Intervention (PsychCentral)
Dyslexia linked to shorter memory trace of previous stimuli (Science Daily)
Hebrew U. researchers gain insight into brain mechanisms underlying dyslexia (Jerusalem Post)
How does dyslexia sound? (TheMarker).
What Musicians Can Tell Us About Dyslexia and the Brain (WIRED).

Merav Ahissar

Professor

Phone: +972-2-5883409
Address: The Edmond and Lily Safra Center for Brain Sciences
The Suzanne and Charles Goodman Brain Sciences Building,
Level 1, Room 1103, Edmond J. Safra Campus,
The Hebrew University of Jerusalem, 9190401

Winners announced for the ELSC photography competition